Manufacturers know that maintenance is important. The numbers reflect that. According to a study in the International Journal of Production Economics, maintenance costs account for 15–40% of production costs (Löfsten, 2000).

And it’s well worth it. According to Buildings, deferred maintenance is massively expensive. Running a machine to failure can cost anywhere between three and 10 times as much as regular preventative maintenance. Not to mention the enormous opportunity cost of lost productivity.

A good maintenance plan is critical for preventing breakdowns. Planned maintenance keeps maintenance teams ahead of machine breakdowns and avoids costly unplanned downtime. Diligent maintenance managers keep a careful eye on their production lines and prioritize tasks in their maintenance plans. Availing themselves of the best tools can help them both monitor their machines, and understand which machines they should prioritize for maintenance.

With a predictive maintenance system like AiSight’s machine monitoring solution, maintenance managers have a steady eye on their machines, every hour of every day, and can check up on their machines from anywhere, no matter the distance. Our predictive maintenance solution detects abnormal vibrations, magnetic fields, and temperature variations, and can discern not only that a needs maintenance, but when it needs it, what kind of maintenance it needs, and what’s caused the abnormal readings.

With this much information in hand, better planned maintenance is easy. It’s possible to optimize maintenance plans, increase productivity, organize maintenance schedules, optimize turnaround schedules, eliminate emergency maintenance, and seamlessly onboard digitization projects.

1. Optimize maintenance plans

Every plant pours resources into maintenance. To keep the plant producing, this is absolutely worth it! But that doesn’t mean that we can’t optimize where our resources go to get the best returns.

Resources dedicated to maintenance includes both the work of dedicated maintenance technicians, and the money dedicated to maintenance.

Optimize labor allocation for maintenance

Maintenance technicians are the everyday heroes who keep production lines running. When we plan maintenance, we want to focus technicians’ efforts on high-impact maintenance that keeps lines not only running, but running perfectly.

With a predictive maintenance solution like AiSight’s, maintenance technicians get the support they need to drive directly to the heart of maintenance issues and make repairs that will keep machines running, optimize asset care, and improve processes.

Save money on planned maintenance

When you can plan maintenance ahead of time, you can have the parts on hand exactly when you need them. With perfect information, it's possible to improve maintenance efficiency and reduce overhead by using JiT deliveries.

Not only that, we can avoid keeping parts on hand just in case. When we know which machines need maintenance, we also know which machines don’t need maintenance. That means that we can reduce overhead by reducing overstock.

Want to see real-world cases of AiSight's solution predicting downtime and easing maintenance planning? Our case studies are available here.

2. Increase productivity with planned maintenance

Production lines are efficient machines, in and of themselves. Each machine integrated in the line is an essential part of the operation of the whole line.

The upshot is, if one machine breaks down, the whole line could break down. This is the number one cause of unplanned downtime, and exactly what we all want to avoid by using planned maintenance.

Keep production lines running

A production line is a complex machine, incorporating the coordinated actions of many complex machines, each itself incorporating the coordinated actions of many machines. If one part of one part breaks down, the whole line can go down.

Planned maintenance should be able to prevent the small breakdowns that lead to greater breakdowns. Our machine monitoring solution keeps eyes on all rotating equipment at all times, and provides immediate alerts when a machine exhibits abnormal behavior indicative of a future breakdown.

Keep utilities in service

It's also possible for systems outside of the line itself to cause unplanned downtime. Compressed air, power generators, heating and cooling, and ventilation systems are not directly part of production lines, but are necessary to the continued function of the line. A failed ventilation system, for example, could force a building evacuation—or worse.

We need planned maintenance to account for utilities too. We want to treat them with the same care as our productive machines. That means our maintenance plans have to include utilities. Luckily, it's also possible to monitor these systems with AiSight's predictive maintenance solution.

Want to see how AiSight's predictive maintenance solution can increase productivity in your industry? Take a look at our industry pages here: textiles, FMCGs, wood processing, and textiles.

3. Organize maintenance schedules

Maintenance managers schedule planned maintenance in weekly and monthly plans based on observations of machines, logged into scheduling tools such as SAP systems. They use these maintenance schedules to coordinate daily tasks for maintenance technicians. Organizing this schedule is critical to implementing quality planned maintenance.

Know what maintenance to schedule

Daily observations of machine conditions are essential for informing which maintenance tasks are scheduled when. Does a task look urgent? It’s scheduled sooner. If something can wait, it will.

A robust machine monitoring system like AiSight’s is an asset in this capacity. Our sensors detect imbalances invisible to the naked eye. Our algorithms are trained to identify root causes and provide advanced warning of machine malfunctions. Access to this kind of information, eliminates uncertainty. Organizing tasks in a planned maintenance schedule, therefore, becomes an easier task.

Eliminate unplanned maintenance interruptions

One of the greatest challenges for planned maintenance is accounting for ad-hoc repairs. While maintenance technicians work on their daily tasks, production lines may still run. While a line is running, it’s possible for any part of it to malfunction. This draws maintenance technicians away from their planned maintenance tasks to deal with urgent maintenance issues.

Here, too, our machine monitoring solution is an asset. When we can predict malfunctions ahead of time, we effectively eliminate ad-hoc repairs. That means there’s nothing to draw maintenance technicians away from their daily tasks, and planned maintenance can continue as planned.

4. Optimize turnaround time in planned maintenance

Periodically, plants have to shut down production for scheduled maintenance. This critical part of plant operation is an opportunity for maintenance teams to have the run of the plant and perform maintenance everywhere, with no interruptions.

We call the time it takes to complete this period of all-out planned maintenance ‘turnaround’. A quicker turnaround is better—we want to complete maintenance tasks and get the plant producing as quickly as possible. Every minute the plant isn’t producing is a loss.

Know machine conditions to make planning maintenance easier

Shutting down a plant for maintenance presents a huge opportunity cost. We want to limit that cost. It’s critical, therefore, to plan maintenance for these shutdowns immaculately. Going over turnaround time is not acceptable.

When we have clear knowledge about exactly what maintenance each machine needs, we can plan accordingly. With a machine monitoring solution feeding us the detailed information about machine faults that we need, we eliminate the risk of extra downtime costs brought on by nasty surprises. We can plan turnaround down to the hour.

Faster turnaround for planned maintenance

With clear information from our machine monitoring solution, not only can we make a precise maintenance plan, we can pull off a faster turnaround.

During a typical scheduled maintenance shutdown, maintenance technicians will perform preventative maintenance on a large set of machines. This is worthwhile—it prevents breakdowns in the future.

But what if we already know what’s going to break down in the future? With a predictive maintenance solution, we do know. If we know which machines are at risk of breaking down, we can dedicate preventative maintenance to those machines, while at the same time avoiding redundant preventative maintenance on machines that are already in perfect working condition.

5. No more emergencies with planned maintenance

While the best laid plans may still go awry, planned maintenance can prevent a lot of emergency maintenance. Planned maintenance is all about keeping on top of maintenance. With the best plan, informed by a predictive maintenance system, it’s possible to all but eliminate maintenance emergencies.

No more night calls for emergency maintenance

Here’s a story maintenance and production managers know all too well.

You’re reclined on a white sandy beach, thinking about... nothing. Somewhere, far across the crystal-clear waters of the bay, a bell tolls, tinny and cheap. It tugs at some distant corner of your consciousness. With a sinking feeling, your sense of responsibility comes loose.

You sit up. It’s suddenly dark; the bell is closer, chiming in your ear, demanding your attention. It’s your cellphone. You answer. It’s the night shift at the plant. Something broke.

The dream is over. You squint at your phone’s screen. It’s three in the morning. Time to go to work.

If you’d known this problem was coming a month ago and planned maintenance accordingly, you’d still be asleep.

Planned maintenance, not reactive maintenance

At its best, planned maintenance is exactly that—planned. Reacting, rather than acting, represents a breakdown in planning. An airtight plan should account for all variables that can lead to the emergencies we need to react to.

With our machine monitoring solution, knowing those variables is possible. Planned maintenance can proceed according to plan. This presents significant knock-on effects—not only do you not have to wake up at 3am to deal with emergencies, you won’t face the demands of day-to-day reactive maintenance that disrupts your maintenance schedule. You can write that in stone.

6. Digitization and Industry 4.0 in planned maintenance

Industry 4.0 is the inevitable outcome of the Fourth Industrial Revolution—the implementation of digitization, IIoT, and AI in industry. This is the future, it’s happening right now, and it’s changing everything about planned maintenance.

AiSight is a part of this wave of change. Our solution leverages AI and IIoT connectivity to monitor machines and predict malfunctions. Planned maintenance benefits from the advantages our solution presents. These benefits are realized not only through better maintenance planning, but in planning for further innovation.

Planned time to onboard and scale digitization projects

Innovation is an active process. Like maintenance itself, it’s worth it. But it takes time and resources that could otherwise be dedicated to production.

Planned maintenance presents a model for success that innovation projects can follow. Onboarding and scaling digitization projects can take real work, during which time production may have to halt. A carefully planned rollout, availed of the best information provided by our predictive maintenance solution, can proceed in an efficient, predictable manner, with minimal downtime. Just like planned maintenance.

If you’d like to read more about successfully rolling out digitization projects, you can read our series on the topic here.

Plan to keep up with the competition

Planned maintenance is critical for ensuring any manufacturer’s optimal productivity. Furthermore, better planned maintenance will improve productivity through prevented downtime and quicker turnaround.

We all want improved productivity!

Innovation towards that end is an inevitability. Planned maintenance offers a distinct competitive advantage, and adopting the latest innovations in maintenance planning is necessary to maximize efficiency.

Takeaways for planned maintenance

The future of planned maintenance includes predictive maintenance. An advanced machine monitoring system, capable of detecting faults, figuring out root causes, and alerting you to problems before they cause breakdowns, is a game changer for maintenance teams everywhere.

With the power of predictive maintenance, you can optimize maintenance plans, increase productivity, organize maintenance schedules, optimize turnaround schedules, eliminate emergency maintenance, and seamlessly onboard further digitization projects. AiSight’s predictive maintenance solution helps you do all of the above.

Let’s get started.

Ungeplante Ausfallzeiten von Produktionsanlagen kosten Geld und schmälern Ihre Gewinne auf lange Sicht beträchtlich. Fest steht, dass Ausfälle von Maschinen und Anlagen eine ernsthafte Bedrohung für die Industriebranche darstellen. Es gibt nie einen guten Zeitpunkt, eine Maschine außer Betrieb zu nehmen, um Wartungsarbeiten vorzunehmen. Doch selbst die robustesten Anlagen benötigen regelmäßig Instandhaltungsmaßnahmen.

In den letzten Jahren wurden die Wartungsarbeiten durch neue Technologien im Rahmen der Industrie 4.0 optimiert. In dieser dreht sich alles um Daten, nämlich wie diese gesammelt, analysiert, interpretiert und angewendet werden. Die vorausschauende Wartung ist ein wichtiger Bestandteil der Industrie 4.0. Denn es geht darum, Daten zu nutzen, um die Anlagen im Optimalzustand zu halten und den Wartungsbedarf vorab zu erkennen. Daten sind die Währung unserer Zeit und leiten eine neue Ära industrieller Abläufe, intelligenter Fabriken und revolutionierter Arbeitsweisen ein.

Vorausschauende Wartung – Predictive Maintenance

Die vorausschauende Wartung ist die fortschrittlichste Form der Instandhaltung, welche auch als Predictive Maintenance bekannt ist. Unter vorausschauender Wartung versteht man den Einsatz datengesteuerter Wartungsmethoden, die den Zustand Ihrer Maschinen analysieren und dabei helfen, Fehlfunktionen, Störungen sowie den Zeitpunkt von erforderlichen Wartungsarbeiten vorherzusagen. Es wird Künstliche Intelligenz eingesetzt, um den Zustand Ihrer Produktionsanlagen in Echtzeit zu kontrollieren. Dank Machine Learning-Algorithmen können Maschinenparameter in der Folge optimiert und Betriebsstörungen verhindert werden.

Die vorausschauende Wartung verfolgt einen proaktiven Ansatz, um Störungen oder Schäden an Ihren Maschinen zu beseitigen, bevor sie zu Problemen führen. Dies steht im Gegensatz zu vorbeugenden Wartung, welche unabhängig davon erfolgt, ob ein Problem vorliegt oder nicht. Im Unterschied dazu gibt es auch das Konzept der reaktiven Wartung, welche lediglich nach einer Produktionsunterbrechung erfolgt.

Hier ein plakativer Vergleich: Stellen Sie sich vor, Sie bringen Ihr Auto basierend auf Echtzeitmessungen von aktuellen Temperatur-, Vibrations- und Flüssigkeitsmessungen zur Inspektion in die Werkstatt, anstatt alle paar tausend Kilometer zur sogenannten vorbeugenden Wartung in Ihre Autowerkstätte zu fahren. Wie gefällt Ihnen dieses Gedankenspiel?

Durch den Einsatz einer vorausschauenden Wartung kann im Voraus vorhergesagt werden, wann eine Ihrer Maschinen mit hoher Wahrscheinlichkeit ausfallen wird. Darüber hinaus kann die Ursache (Root Cause Analysis) für diesen Ausfall ermittelt werden. Der klare Vorteil: Die Wartung der Anlagen kann geplant werden, bevor dieses Ereignis eintritt und Ihnen somit enorme Kosten sparen.

Mit vorausschauender Wartung zur Reduktion von Maschinenausfällen

Das bedrohliche Szenario ungeplanter Ausfallzeiten plagt Produktionsbetriebe seit Jahrzehnten. Schließlich bedeuten sie – wenn auch noch so geringfügig – einen Produktivitätsverlust, der sich auch auf das Endergebnis auswirkt. Steigende Ausfallkosten in Verbindung mit häufigen Stillständen von Maschinen stehen ganz oben auf der Liste der Faktoren, die zu einer niedrigen Rentabilität in der Produktion beitragen. Ungeplante Ausfallkosten sind somit einer der größten Kostenverursacher in der Produktion. Die vorausschauende Wartung kann hier zu einer erheblichen Reduktion der Maschinenausfälle beitragen.

Künstliche Intelligenz statt Wartungspläne

Früher waren Wartungspläne in der Industrie die beste Option zur Vermeidung von Ausfällen. Mittlerweile gibt es dank Künstlicher Intelligenz technologische Lösungen, die es ermöglichen, diese ungeplanten Ausfallzeiten zu vermeiden. Durch eine vorausschauende Wartung Ihrer gesamten Produktionsanlagen können Machine Learning-Algorithmen, basierend auf den gesammelten Datensätzen, Ausfallzeiten Ihrer Anlagen vorhersagen.

Dadurch haben Ihre Wartungsmitarbeiter*innen die Möglichkeit, Kapazitäten auf andere Anlagen zu verlagern und Wartungsarbeiten zu Zeiten mit den geringsten Auswirkungen auf die Produktion zu planen. Bei Bedarf können Ihre Wartungsmitarbeiter*innen auch rechtzeitig Ersatzteile für die betroffene Anlage bestellen, ohne, dass es zu einem Stillstand Ihrer Produktionsanlagen kommen muss.

Senkung der Wartungskosten mit vorausschauender Wartung

Vorausschauende Wartung macht eine fortschrittliche Erkennung von Störungen oder Fehlern sowie die Wartung von Maschinenteilen möglich. Dadurch können teure Reparaturen deutlich reduziert werden. Darüber hinaus zeigt sich, dass eine effiziente, vorausschauende Wartung zusätzlich zu einer längeren Lebensdauer Ihrer Anlagen beiträgt.

Insbesondere in unserer Post-Covid-Wirtschaft sind Kosteneinsparungen wichtiger als je zuvor. Unternehmen, die sich finanzielle Flexibilität verschaffen wollen, müssen unnötige Kosten vermeiden. Die langfristige und nachhaltige Senkung der Wartungskosten mittels vorausschauender Wartung ist einer der effektivsten Wege.

Denn eine vorausschauende Wartung unterstützt Sie nicht nur bei der Reduktion von Ausfallzeiten und Stillständen in der Produktion, sondern sie verringert zudem auch die Anzahl größerer Reparaturen. Dies schlägt sich nicht zuletzt in geringeren Überstundenkosten und einem wirtschaftlicheren Einsatz von Ihrem Wartungspersonal nieder.

Optimale Auslastung und verbesserte Kennzahlen

Die vorausschauende Wartung ermöglicht eine bessere Auslastung Ihrer Wartungsmitarbeiter*innen und führt somit zu einer Steigerung der Arbeitsproduktivität. Diese haben durch die vorausschauende Wartung mehr Zeit, sich auf wichtige Wartungsaufgaben zu konzentrieren und müssen ihre wertvollen Ressourcen nicht mehr für die manuelle Erfassung der Daten aufbringen. Da es weniger Notfalleinsätze gibt, können Sie Ihre Ingenieur*innen effizienter einsetzen und kritische Arbeiten als Teil der regulären Aktivitäten einplanen.

Dies verbessert zudem auch Ihre Schlüsselkennzahlen in Bezug auf Betrieb und Wartung, wie zum Beispiel die Durchschnittszeit zwischen den Ausfällen, Mean Time to Failure (MTTF), sowie die Durchschnittszeit für die Reparatur, Mean Time to Repair (MTTR).

Um eine optimale Gesamtanlageneffektivität (GAE) - im Englischen auch als Overall Equipment Effectiveness (OEE) bekannt - zu erreichen, sollten Sie auf Grundlage tatsächlicher Informationen über den Zustand der Anlagen Ihre Wartungsarbeiten planen und nicht basierend auf einer rein hypothetischen Lebensdauer.

Dank vorausschauender Wartung zum Wettbewerbsvorteil

Ein genaues Auge auf die Konkurrenz zu haben, gehört in jedem Produktionsunternehmen zur Tagesordnung. Um wettbewerbsfähig zu bleiben, greifen Herstellerbetriebe zu den unterschiedlichsten Maßnahmen. Manche Betriebe fokussieren sich auf die Qualität der Produkte, um sich von der Konkurrenz zu unterscheiden. Andere wiederum konzentrieren sich darauf, auf einen vorbildlichen Kundenservice anzubieten oder versuchen sich über den außergewöhnlichen Wert oder Preis von Mitbewerber*innen abzuheben. Es ist schon lange kein Geheimnis mehr, dass vorausschauende Wartung Ihnen einen beträchtlichen Wettbewerbsvorteil bieten kann.

Intelligente Fabriken für mehr Nachhaltigkeit

In intelligenten Fabriken - auch als Smart Factories bekannt - können Sie durch eine kontinuierliche Überwachung Ihrer Maschinen schnellere und effizientere Produktionszyklen fahren und sich somit von der Konkurrenz abzuheben. Das Ziel der vorausschauenden Instandhaltung ist es, den Zustand Ihrer Maschinen jederzeit von überall im Auge behalten zu können. Durch die Ursachenanalyse haben Sie die Möglichkeit, jegliche Störungsursachen mühelos zu ermitteln. Außerdem kann Ihr Unternehmen durch eine effizientere Nutzung vorhandener Ressourcen auch Engagement für Nachhaltigkeit unter Beweis stellen. Ein Thema, dem zukünftig ohnehin noch viel mehr Raum geboten werden darf. Sie sehen schon, vorausschauende Wartung ist viel mehr als die bloße Vermeidung von Ausfallzeiten.

Haben wir Ihr Interesse geweckt? Sie möchten den Zustand Ihrer Maschinen effektiv überwachen, um Ausfallzeiten vorherzusagen und Ihre Maschinennutzung zu optimieren?

Wir freuen uns auf ein persönliches Gespräch!

© 2022 AiSight GmbH. Alle Rechte vorbehalten.

Telefon: +49 (0) 30 40363399

Website: https://aisight.de

This is the second part of our series of articles on how to escape pilot purgatory, and how to successfully scale digitization projects. You can find the introduction here, and part one here.

We launch pilot projects because we want to innovate. According to McKinsey, 84% of CEOs believe that innovation is critical to growth. Meanwhile only 6% of CEOs are satisfied with their innovation performance.

What accounts for this gap between conviction and performance?

Remember, only about 30% of companies that launch IIoT pilot projects are able to scale them. As an act of innovation, scaling a digitization project will run into the problems faced by firms’ attempts to innovate in general—no matter how successful the pilot project was.

This is a problem of strategy—or lack thereof. A pilot project can address real problems and deliver demonstrable results, but this is only a tactical success. Rollout requires firm-wide, big-picture thinking: an innovation strategy.

For businesses, strategy requires a lucid understanding of three things: the organization's goals, the market, and the organization's own strengths. From there, all that’s left is to execute. This is when we can scale our pilot projects! Applied to rolling out digitization projects, innovation strategies clarify objectives, focus efforts, and connect diverse stakeholders.

HOW INNOVATION STRATEGIES AFFECT ROLLOUT

There’s a legendary story in Silicon Valley that illustrates how innovation strategies work.

In 1973, Xerox introduced the first desktop computer to the world. The Alto had a bitmapped screen, a mouse, a Graphical User Interface (GUI). It could connect to other Altos through Ethernet. It ran a word processor. It could send emails. It even had a paint program. It had everything we expect from desktop computers. It should have been revolutionary.

It sold 120 units.

The Alto was the product of Xerox’s legendary Palo Alto Research Center (PARC)—primordial ooze for computer development. PARC invented first after first for computing, and put it all together in the Alto. But the business side of Xerox never saw the Alto's potential, didn't appreciate PARC's strengths, and remained disconnected from their research department's miraculous work. That Xerox never capitalized on the Alto may be the biggest strategic blunder in the history of computers.

But was it really?

Consider Xerox’s position in 1973: they were a printer company! Their goal was to sell printers. They were familiar with the printer market. They made great printers. And they, therefore, sold a lot of printers. Around the same time that they were creating the Alto, Xerox PARC also invented a laser printer. Xerox had no problem bringing this innovation to market because that was their strategy all along.

The inspiration for AiSight came to one of our founders thanks to his experience at a major automotive company. The automotive sector is ruthlessly competitive. To survive, automakers push constant innovation in material sciences, engineering, and even marketing—all unified behind a clear objective: selling more cars.

To this end, automakers also want to reduce downtime on their production lines. But developing a proprietary predictive maintenance system isn’t economical, and creating one to provide to other manufacturers is not part of their strategy. This is where AiSight comes in—we provide the predictive maintenance solution that fits their innovation strategy.

CLARIFIED OBJECTIVES OF ROLLOUT

When we consider the Alto and the laser printer, we see two Xerox innovations; one consistent with their innovation strategy, the other not.

With the benefit of hindsight, we know how big the Alto could have been. But in the early ‘70s, the desktop computer was an unproven product, with a nonexistent market, that Xerox had no ability to mass produce. While selling the Alto could have made Xerox an alternate-timeline Apple, it also could have distracted from their core business, soaked up capital, and weakened their brand. Xerox’s strategy protected them from that outcome and guided their innovation in the direction that worked for them.

The issue here isn’t that Xerox didn’t innovate—they did. The issue isn’t that they didn’t have an innovation strategy—they did. The issue is that Xerox knew their objective very clearly. It just wasn’t selling desktop computers.

When we launch a pilot project, we're more likely to successfully scale if we do so with a big picture objective in mind. A company with an innovation strategy will know that objective, and rally around it. The result is an organization that pulls together towards innovation. This is an atmosphere in which our digitization projects can scale.

FOCUSED EFFORTS AND INNOVATION STRATEGIES

Before an organization can work together on innovating, leadership has to want it. This reinforces the value of getting high-level decision makers involved in step one. They have the influence to create and direct an innovation strategy. They also have the ability to direct resources towards it.

Leaders can, for example, designate an innovation task force. Any team introducing an innovative solution without the support of a strategy runs into the reality of day-to-day business: it’s busy. Nobody has time to divert from their normal duties. There are always short-term goals—quarterly earnings, product launches, clients, coworkers, lunch—the big picture can get lost in the minutiae without people actively keeping it in view. The innovation task force can take care of the new responsibilities that innovation demands.

This, in turn, allows the seamless integration of innovation into operations—both in innovating, and in using innovations. Putting innovations to use—that’s rollout! It also involves introducing our project to a whole lot of stakeholders.

CONNECTED STAKEHOLDERS

Our project is out of the silo. The innovation strategy guiding us has built the lateral connections throughout the organization that we’ll need to scale. This is where we get the stakeholders involved—from the managers who need to know about it, to IT who will integrate it, to the colleagues who will use our innovation every day.

That’s the topic of our next article: The Stakeholders. Rollout will—and should—shake things up. We want to keep everyone informed and on board.

Keep an eye out for part three of this series.

In the meantime, why not get started on your own successful rollout?

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

This month, we’re making our first appearance at Hannover Messe. This is a big deal for us—Hannover Messe is a big deal! To understand why Hannover Messe is so important, we dug into its history. It's a story with humble beginnings 75 years ago. And somehow, it's still far from over.

Hannover Messe is the largest industrial technology fair in the world. Each year it attracts roughly 6500 exhibitors and 250000 visitors, from all over the world. It’s a must-attend event for industry’s decision makers; it’s a chance to connect with the industries of the future.

But in its first year, guests called the fair the Fischbrötchenmesse (fish sandwich fair). That doesn’t sound like the most important fair in the world for industrial technology—or anything but fish sandwiches. And it shouldn’t. Hannover Messe’s origins are humble—rooted in destruction and poverty, far from any celebration of industry or technology. The story begins in post-war Germany.

Before the Hannover Messe

In August, 1945, the war in Europe was over. Given the unprecedented scope of destruction, the threat of renewed aggression in Europe, and the ongoing war with Japan, the Allies adopted a clear demilitarization policy in Germany. This included dismantling all heavy industry capable of contributing to any war effort. Germany’s prior mobilization towards total war, meanwhile, had effectively oriented all industry towards war production. For the next two years, the Allies dismantled and destroyed hundreds of German industrial facilities.

These were lean years. European productivity focused on rebuilding. Across the continent, the economy failed to rebound. Agricultural production in Germany declined, necessitating food rationing. The Allies saw that this situation wasn’t ideal for maintaining peace and stability—it was clear that the plan adopted at the end of the war had to change.

“An orderly and prosperous Europe requires the economic contributions of a stable and productive Germany” —General Lucius D. Clay, US Army, administrator of occupied Germany

In August, 1947, the Allies reversed course on industry in Germany. In Hannover, the British occupiers saw the value in holding an industrial fair. Together with the Lower Saxony economy ministers, they established the first Hannover Messe—then called Exportmesse (Export Fair), but already using its trademark Hermes logo—in a collection of aircraft hangars south of the city. They even exempted the fair from food rationing. Visitors gorged on fish sandwiches. The Fischbrötchenmesse was born.

Messen and miracles

That fair was a success. It contributed to the revival of German industry—but it wasn’t alone. Once controls on German industry lifted, a number of factors favorable to economic development came together in a perfect storm: a skilled population, access to technology, high capital investment, and timely reforms. The result was an economic miracle, and a miracle for the Hannover Messe.

The war and deindustrialization efforts had left the German economy as something of a blank slate, ready to come to life. The skilled labor pool, growing thanks to deportations from Eastern Europe, was ready to work. Factories had been destroyed, but that presented two sides of a blessing in disguise: there was nothing to maintain, and nothing to buy. There was, therefore, nothing to do but invest in new industry.

Upon this blackboard, Ludwig Erhard sketched out a map for Germany’s economic renaissance. This called for two measures: a new currency, the Deutsche Mark, which would maintain export prices while wiping out debt; and an end to price controls implemented in the 1930s. Almost immediately following these reforms, profits on exports surged and consumer goods reappeared in German shops.

Soon after, the Americans introduced the Marshall Plan—an expansive program to restore the European economy through economic stimulus and modernization. Over the next two decades, economic miracles unfolded across Europe. In Germany, the Wirtschaftswunder was especially pronounced; industry flourished—and so did the Hannover Messe.

Changes and names

By 1950, the Exportmesse had to broaden its scope beyond export industries. Industry in Germany was back, increasingly producing for an increasingly affluent domestic market. That year, the fair even included a whole new section dedicated to what they called Büroindustrie (office industry).

In response to the growth and fracturing focus, the Messe split, into the Export Fair, and the German Industry Fair. A few years later, the two sides of the fair reunited under the latter’s name. That lasted until 1961, when the Messe again changed its name to the name we all know—Hannover Messe. This was, by then, the name the world knew; the change of name reflected Hannover Messe’s stature and an established awareness of its brand as an industry fair. There was no longer any need to spell it out.

Landmark growth of Hannover Messe

In 1958, Hannover Messe completed their first landmark: the Hermesturm, an 88-meter-high tower and observation deck with panoramic views of the entire fairground and the city beyond.

The fairground itself was growing too. By the late ‘60s, the section for so-called office industry had grown beyond the existing facilities’ capacity. To house it, Hannover Messe thought biggest. In 1970, they completed construction of what was then the largest exhibition hall in the world: Halle 1: CeBIT (Centrum für Büro- und Informationstechnik). The name CeBIT, then, reflected the IT-focused part of the fair housed in Halle 1.

By 1986, CeBIT had outgrown not only Halle 1, but halls 2, 18, 3, and finally Hannover Messe itself. That year it branched off, becoming a fair dedicated solely to IT, held a month before the original Hannover Messe. Over the next two decades, CeBIT would become the world’s point of introduction to numerous new technologies, and the largest IT fair in the world. Attendance peaked in 2001 with 830000 visitors.

Hannover Messe to the world, and to the future

By 1980, industry around the world was more interconnected than ever—and there was no sign that this would stop. To facilitate international cooperation, Hannover Messe introduced its partner countries initiative, inviting Brazil to present that year. Every year since, one country has presented their products, culture, and technology to the world at Hannover Messe. Portugal is the Hannover Messe 2022 partner country.

The fair's mandate for internationalization has only expanded. In 1985, Hannover Messe launched a subsidiary, Hannover Messe International, tasked with operating Hannover Messe events at expo centers outside of Germany. Since then, HMI has brought Hannover Messe to markets around the world.

Not satisfied with reaching every corner of the earth, the Messe also reaches for the future. To this end, in 2004, they introduced the Hermes award for achievements in innovation. Each year, a panel of industrial technology experts selects one participant who has presented a solution that demonstrates not only a high degree of technological innovation, but benefits for industry, the environment, and society; cost-effectiveness; and readiness for implementation. The prize includes a 100000 Euro reward, making it one of the richest technology prizes in the world.

Since then, Hannover Messe has lived up to the spirit of that award by featuring leading-edge developments. The Messe is, for example, arguably the cradle of the fourth industrial revolution. In 2011, members of the Forschungsunion Wirtschaft – Wissenschaft (Research Union for Economy and Science) introduced Industry 4.0 and the Internet of Things at the conference. The Messe made Industry 4.0 and IoT themes of later fairs, in 2013 and 2014 respectively. They also took the lead in hosting an online version of the fair—a feat which prepared them for the inevitable closure of in-person events in 2020 and 2021.

Hannover Messe 2022

In 2022, it’s been 75 years since Hannover Messe’s inception. It’s come a long way from the Fischbrötchenmesse. Each year, it hosts 1400 events and 1500 international speakers. It attracts hundreds of thousands of exhibitors, visitors, journalists, and politicians. Two-thirds of these are decision makers; a third have firm investment plans. They make millions of business connections that span the globe.

We're going to be there. And we want you to come too. Register here and get your free tickets to Hannover Messe 2022. We'll see you there!

‌© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

At AiSight, we’re as serious about personal health as we are about machine health—extremely. We know that healthy team members are happy and productive team members. And that’s exactly what each of us want—both for ourselves, and for the sake of the team. That’s why we include opportunities for health, activity, and education in our benefits package.

But we’re always looking for new ways to help. As part of our policy of promoting personal growth, we hold AiSight Academies—learning sessions taught by team members or outside experts on non-work-related topics. At a recent AiSight Academy, we reached out to the experts for guidance. Who better to contact than our health insurance provider, TK? They put is in touch with Patricia Wolf, a nutritionist from Moveup Gesellschaft für Gesundheits Management. Moveup is an independent agency that brings innovative health solutions right into the workplace, keeping teams healthy, mobile, and alert.

Patricia treated us to an informative remote-learning session on meal prep. It included a demonstration of the importance of healthy nutrition, the what and how of meal prep, and showed us how to make a prep kit, structure our days around meal prep, and prepare a few delicious meals. Here’s what we learned.

We’re delicious, but are we nutritious?

Patricia’s lecture began with an informal survey, asking each member of the team to rate the healthiness of their diet, from 1-10. Scores ranged from 5 to 11. Like we said, we take personal health seriously. But that didn’t mean we didn’t still have a lot to learn—especially considering how the pandemic and working from home has changed our lifestyles.

For many people, working from home has eliminated a period of activity built into our days—our commutes—with predictable impact on our health. But it’s also eliminated the structure of our days. Without a work schedule to adhere to, we’ve lost the meal schedule that went with it. That’s left us eating odd food at odd times.

When we eat compulsively, rather than deliberately, we take the path of least resistance. There are many reasons why we eat. Hunger, Patricia showed us, isn’t even the leading reason—that’s boredom. Plus, eating makes us happy; it releases hormones that affect our feeling of well-being. The upshot of this is that eating bad food makes us feel bad.

Processed foods are easy food. They might even taste good. But when we grab a quick and easy piece of processed, we don’t really get what we want. Processed foods lack the nutritional content to actually satiate. Instead, they’re full of artificial ingredients, trans fats, sugars, salts, and preservatives. This is where they affect our health—in the short term they leave us tired, cause headaches, ruin our ability to concentrate, and cause problems everywhere from the surface of our skin to the depths of our bowels. Long term, the picture is even worse.

So, we need to eat better. We also need something fast, affordable, healthy, edible—preferably even delicious. Hence, meal prep.

What and How?

When we prepare our own food, not only do we know what isn’t in it—all the stuff in processed food—we know what is in it. The ideal meal is half vegetables, and contains proteins, complex carbs, and healthy fats. The result should be satiating and nutrient rich, with the fat to carry fat-soluble vitamins, and the fiber to regulate blood sugar.

Patricia laid this out in an easy-to-follow formula for meal prep. Just check off each of 1. vegetables, 2. protein, 3. complex carbs, and 4. sauces and toppings. To illustrate how this works, she provided several recipes. A quinoa and chickpea layer salad, for example, combines plenty of veggies with two sources of double-duty protein and complex carbs, and some healthy fat via an olive-oil-based sauce.

With cooking sorted, Patricia also gave us a look at the other side of meal prep: storage. A prepared meal is only good as long as you can eat it. There's a science to storing food safely, for as long as possible, while preserving its best qualities—flavor, texture, and nutritional value. When done right, we can prepare delicious and nutritious meals weeks in advance, and still get the full benefit of eating fresh food.

Enjoy your meal, and your time

The meal-prep payout comes not just from eating healthier food, but enjoying the act and ritual of eating. Remember, one of the advantages of meal prep is restoring structure to our days. That means appreciating and using the time we save by meal prepping, and the time we spend eating our prepped meals.

This makes meal times punctuation for the day—a chance to relax and recover between fulfilling our responsibilities. In the morning it’s important that we take time to hydrate and relax. At lunch, when we eat our prepped meal, we shouldn’t eat at our desks—we need to take a break, get away from the desk, and use the opportunity to go for a short walk. A healthy, satiating snack in the afternoon will sustain our blood sugar and carry us through the end of the day. At dinner, we can simply incorporate anything we missed in our lunch, and unwind from our day.

These are all important lessons for the flexible work structure of the future. We’re starting to get comfy in the office again, but in some capacity work from home seems here to stay. Healthy, prepped meals will be the same lunch-time assets in the office and at home, and taking time to eat is important no matter where we do it.  Here’s to healthy eating!

Want a job with healthy benefits? Take a look at our openings here.

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

Pilot projects are supposed to lead to more. It’s right there in the name; these are the leaders of soaring ambitions, the work of which lets to projects taking flight.

Of course, a flight without a destination can’t lead to anything.

When we begin our onboarding process, we’re already laying the groundwork for a successful rollout. This is our opportunity to figure out our destination: the use case. The process calls for clear and open communication of needs and capabilities. The two meet at a well-defined use case for the solution, with clear objectives, demonstrable value addition, and enthusiastic participants.

Get Objective

In a classic episode of The Simpsons, a huckster pitches Springfield on building a flashy new monorail system: electrified, six cars, glides softly as a cloud, lots of cushy jobs. While the rest of the town is swept up in monorail fever, Lisa Simpson asks the huckster to, “explain why we should build a mass-transit system in a small town with a centralized population.”

Indeed, Lisa.

The world is long on exciting solutions. We make more every day. But an exciting solution is only the right solution if it actually solves a problem—otherwise it’s no solution at all. Monorail may be fun, but a small town with a centralized population is a poor use case for monorail. Bike lanes would be a more appropriate solution because they would actually address Springfield’s problems.

The same is true of digital manufacturing solutions. Excitement may be enough to launch a pilot project, but that excitement will fizzle when everyone involved realizes that the solution is a poor fit for extant problems. That’s why it is critical that both parties in a project understand what the solution provider offers, and what the customer needs.

At AiSight we make a predictive maintenance solution that includes plug-and-play vibration sensors and a software dashboard to analyse, interpret and visualize sensor information. It is pretty exciting! But we want it put to appropriate use, meeting our customers’ needs.

That means we want to know about pain points—where there are problems we can solve. High-maintenance machines or machines that require frequent manual interventions are best. For example, we recently completed a validation phase in which we installed sensors on every single machine in a parquet flooring line. There wasn’t a bad use case in the bunch—the kinetic and abrasive work, 24-hour production schedule, and high cost of unplanned downtime made the line a perfect candidate for predictive maintenance.

As expected, this validation phase demonstrated significant added value.

Demonstrating Value

Given the fallibility of launching pilot projects based on fleeting emotions, we would be wise to let the data lead. That means that we should be able to back up the merits of any project with provable added value. When launching a pilot project, therefore, we have to be candid about its costs and benefits.

According to this study from Mckinsey, “61% of respondents see lack of ROI as a major obstacle when implementing Digital Manufacturing solutions at scale.”

Mathematically, there are two reasons a digital manufacturing solution would lack ROI: high cost of investment, and low return. These are two sides of the poor-use-case coin. In communicating our respective solutions and problems, we also have to communicate expectations. This means comparing the cost of the solution to the cost of the problem, and expecting a satisfactory difference.

This is the scientific method at work. Launching a pilot project should include an explicit hypothesis: we will see ROI within these parameters. All the solution has to do in the validation phase, then, is deliver. Upon delivering results, it should be easy to move on to rollout because everyone should have been prepared for that result.

In the case of the parquet flooring line above, each hour of downtime could cost our client up to 20.000€. Since breakdowns were common on the line, we could expect that using our predictive maintenance solution to manage downtime would deliver significant savings. Over six months, our system performed to expectations, delivering 200.000€ in savings. Well worth it!

Now We Can Get Excited

This is our chance to get emotional. We have quantifiable expectations. They look great! If the solution performs in the pilot project, we’d be remiss not to scale.

But can we?

It’s not a given. The ability to launch a pilot project doesn’t entail the ability to scale. There are often plans at work beyond the scope of the pilot project—even beyond the scope of broader rollout.

This is why it’s important to get people at the highest level in companies involved in pilot projects from the outset. If they’re sold on the use case and know what to expect, they too can get excited. This calls for communication not only between parties, but also within the organization implementing the solution.

This is also a matter of that organization’s broader goals. It’s a simple reality that, for better or for worse, for reasons good or bad, scaling might not fit organizational goals. Buy-in from high level stakeholders is not only critical for their approval, but for their ability to set a broader agenda.

The Next Step

With a clear use case, made-to-measure expectations, and high-level involvement, we’ve completed step one. Not only have we cleared the first obstacle to successful rollout, we’ve laid the groundwork for the next step.

That’s the topic of our next article: The Strategy. Companies that take on projects as part of broader innovation strategies are primed to both implement innovative solutions, and to maximize their benefits. Stay tuned for part II of our series for an in-depth look at how strategy enables success, plus examples of the principle in action.

If you're eager to get started, schedule a demo now.

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© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

We have a clear goal at AiSight: eliminating unplanned downtime. It’s a complicated problem. If we could eliminate it with stern words, we would have. It doesn’t listen. So, we adopted a more robust approach, drawing on the diverse talents and skills of an amazing team.

AiSight is a team of specialists—the combined product of our specialized work is the realization of our solution. If you’re a specialist who wants to work at AiSight, we want to hear from you. To give you an idea of how your skills will fit within the structure of the broader team, we’ve prepared this article.

Team AiSight is comprised of four sub-teams: R&D, growth, operations, and admin. Each performs different functions, but each is essential to the function of the company as a whole.

R&D (Hardware and Software)

Within R&D, we have teams developing the hardware and software sides of our solution.

Our Aion sensors are the bedrock upon which everything else at AiSight stands. Our hardware team has equipped each Aion with a triaxial vibration sensor, a magnetic field sensor, and a temperature sensor. All in a sleek package that mounts with magnets and connects to our dashboard through Wi-Fi.

This group of designers and engineers takes care of our sensor’s external appearance, functionality, and firmware. You can find out more about the quality work our hardware team has done here—everything from navigating chip shortages, to developing our own sensors in house, from the ground up.

Meanwhile, our software developers are a team of bona fide magicians. They make sure that the data from the sensors is accessible to our customers in real time, via our dashboard. The dashboard interprets sensor readings for our customers' consumption, and issues alerts when things go wrong—all in a browser-based package.

Software team members work in data science, coding, and cloud applications. Besides developing the software that makes our system so powerful and intuitive, this team is also involved in the initial analysis phase of our onboarding process. This is the moment of truth—not only does predictive maintenance become a reality, we're able to detect preexisting problems in machines.

You can read more about our onboarding process here.

Growth (Sales, Customer Success, Business Development, Marketing)

Our growth team is responsible for connecting our solution with those who need it. They bring automated machine diagnostics to industry.

Our sales colleagues help our customers find the solutions that meets their needs. Not only do they introduce our solution to customers, they communicate what customers need back to the team, so that we can tailor our solution to fit. That means that these team members are databanks of knowledge on our solution—anything customers need to know, sales is prepared to tell them.

While sales team members specialize in contact and education, our customer success team members are there for the duration of our customers’ time using AiSight’s solution—as much a part of the customer's team as our own. This includes every step of our relationship, from the validation phase to company-wide rollout. That means these team members also work closely with software and operations during the onboarding phase. Whatever our customers need, their customer success team member can deliver.

Meanwhile, our business development team builds up strategic partnerships. This strengthens our network in industry, making sure not only that customers find what they need in us, but that we can find what we need in others.

Finally, our marketing team shapes our brand identity. This sweeping act of communication includes work on our website, social media, and all other brand-related content. Their goal: to inform choices. That means that everyone approaching AiSight does so knowing exactly who AiSight is.

Operations

Once our customers have chosen to use our solution, our operations team springs into action. This team is also a key part of the onboarding process we mentioned earlier—their job is to install and integrate our system in customers’ facilities. This means mounting sensors, connecting power, and setting up the connections to monitor the sensors.

Our operations team works every day to ensure that both logistics and installations run smoothly. The result: customers get what they need, where they need it—and it all works. Thanks to them, we can proudly offer a perfect customer experience.

Admin (HR, Recruiting, Office-Management, Finance)

This team supports all the other teams in a variety of specialized ways.

Our HR colleagues take care of our team members. This includes recruiting—bringing new, great, and talented colleagues to AiSight. At the same time, they’re around to encourage and support everyone. That's how we all get the best out of our career paths.

Our office managers’ vision is to make the office as pleasant as possible. They perform all kinds of tasks that the rest of us couldn’t function without. Think of coffee in superhero form.

Finally, our finance team supports AiSight's rapid and sustainable growth. They make data-driven decisions to secure our team’s financial health. Thanks to them we even get paid!

Would you be an asset in any one of the above teams? Take a look at our openings here. If you’d like to know more about applying to work at AiSight, we have an article for that too. Or, why not get started? Send us an application. We’d love to hear from you.

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

AiSight offers a complete predictive maintenance solution. This includes both hardware and software—the sensors that detect anomalous machine behavior, and the dashboard that interprets sensor data, respectively. These two integrated parts of our product are, themselves, products that were subject to their own development processes. In both cases, their successful development depended on one thing above all: requirements.

Competitive and profitable companies need new products to reach the market in the shortest possible time, at minimal cost. These products also need to satisfy customers’ needs or solve their problems. In order to know what customers require, it's necessary to understand their language! Likewise, it's important to translate their language into engineering terms so that everyone involved in the product's design and manufacturing understands what the product will be. Whatever the language, requirements are a constant—the key to the process of generating the right product.

Communication is Key

Imagine that you want to construct the house of your dreams. There are a lot of things that you want: architecture, colors, many rooms, a garage, a backyard, kitchen appliances—all of the elements that compose your place for life. If the builder has no clear understanding of what you want, the house of your dreams will become the house of your nightmares, subject to frustrating construction delays or going over budget. And even if the builder has a perfect understanding of what you want, but he does not know how to explain it to the subcontractors (painters, plumbers, electricians, and so on), then there is huge potential for this building to be a source of issues and headaches.

The illustration above shows how requirements can be a path to success—and how miscommunicating them can become a disaster for a company. The process of aligning requirements is a time-consuming task, but it should not be ignored or given a low priority. A set of features that are not based on market or specific customers’ demands has a big chance of commercial failure. And requirements that are not properly translated into design requirements lead to longer development time or, in the worst case, a recall.

Finally, requirements are not only based on what customers want–they have to meet legal certifications, such as the CE mark for the European market or FCC requirements for the American market. Ignoring governmental regulations is a risk. All of the investment to launch the product will be lost if the product is not approved under the required standards.

Design Requirement Requisites

Once the product's requirements are identified, the next step is to translate them into design requirements. For example, a hardware product has requirements for electronics, for mechanics, for software, for transportation, for storage, for installation, and many other fields. Here are some best practices for writing requirements.

• The requirements shall be simple, short, and clear  - to avoid misunderstandings.
• The requirements shall be feasible - to have a viable product.
• The requirements shall be testable - if we cannot test, we cannot verify that the requirement has been met.
• The requirements shall be complete - missing information will result in a poor design.

Before we begin design according to requirements, we need to validate the requirements. This step is a confirmation that our requirements are the right requirements. In other words, validating requirements ensures that we will design the right product.

Making the Grade

Once everyone is clear on the requirements, we proceed with the design of a prototype according to those requirements.  Then comes verification, when we test the design to confirm that the requirements are met. In other words, during verification we check if we designed the product right. This entails creating test plans and procedures according to the requirements applicable to the prototype.  If the requirements are well written—defining behaviors, constraints, and efficiency and performance metrics—the generated tests will allow us to make an excellent product.

Of course, requirements can change during development. This is, however, part of the learning process—managing requirements is necessary to ensure that communication with all stakeholders remains open, that we track and understand the effects of changes, and that changes ultimately lead to a better-quality product.

In summary, the process of generating and managing requirements is key to developing a successful product in fewer redesign cycles. That reduces both the time to market and overall cost. Mission accomplished!

This process of requirement-driven design has served us well—the proof is in the product. And we're confident it will continue to do so. If you'd like to learn more about how requirements guide development, we recommend this article on the process we undertook to get our CE mark.

Want to talk about our product and its development? We'd love to hear from you.

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

Whether talking about rolling out AI, industrial internet of things, or any other digitization project, there’s a far-too-common story in every case. Someone in a company decides to adopt a solution. They launch a pilot project. The end.

According to this study from McKinsey, only about 30% of companies that launch IIoT pilot projects are able to scale them. The projects that don’t scale are either dropped or languish in so-called pilot purgatory, their potential never realized.

As makers of an IIoT solution, this is a nightmarish outcome. We want people to scale our solution! At the same time, projects that never scale do nothing for the companies running them. Nobody benefits from a failed rollout.

Back in October, 2021, we hosted a webinar, Implementing AI projects - How to Overcome “Pilot Purgatory”, to discuss this problem and propose the conditions necessary for successful rollouts. We encourage you to watch the webinar—it's available with English subtitles. Over the coming weeks, we’ll share the insights from that conversation in this series of articles. Check each following issue for real-world examples and an in-depth look at each condition introduced here.

Given the odds against successful rollouts, how do we avoid the purgatorial fate of the majority? In a word: clarity. Of course, achieving that clarity means a lot of work. It means having a clear use case, a clear strategy, clear understanding between stakeholders, a clear value contribution, and a clear path toward broader integration.

We can satisfy these conditions step by step. Here are the five steps to successfully implement a digitization project.

Use Case

The tragedy of pilot purgatory is that pilots are supposed to lead the way to more. But without a clear understanding of where a pilot project is going, we can hardly expect it to lead to anything. The groundwork for a successful digitization project, therefore, starts before the pilot project even begins, during onboarding.

Before we even attempt to validate a solution, we have to understand our use case. Any solution is only as good as it is applicable to a problem. A well-defined use case is essential to avoid the inappropriate and ineffective application of a solution. The use case, therefore, should come with clear objectives. Added value should be provable, or already proven.

Strategy

Clear goals for the pilot project itself are important. But meeting goals alone isn’t enough to force a successful rollout. Pilot projects that proceed in isolation are unlikely to proceed to rollout. The goals of the pilot project must nest into a set of broader goals.

Companies are best served to take on projects as part of broader innovation strategies. This works on multiple levels: it’s easier to appreciate the benefits of a project within the context of a larger strategy, it’s easier to integrate a successful project in a system that’s primed to take it on, and it’s easier to get all stakeholders involved if the pilot project isn’t siloized.

Stakeholders

Rollouts can be vast undertakings. They involve many stakeholders, from all over a company. It’s critical to keep them all engaged in the entire process, from onboarding on.

Top management sets the broader strategy and will ultimately decide a project’s fate. The people who actually implement a project will have a view to its efficacy and should have a clear understanding of its goals. Meanwhile, the people who actually use the solution will provide important insight on the use case and the success of the project.

Value Contribution

Any successful pilot project should demonstrate value contribution. This means benchmarks: KPIs, time to ROI, cost vs savings. It also means showing qualitative value—does the project make the product better? In the end, does it help customers?

Of course, any value contribution is only as good as it is demonstrable. A demonstration requires an audience. The benefits of scaling a project may be clear, but without engaged stakeholders to see that benefit, it’s just another tree falling unheard in the woods.

Integration

Once a pilot project is complete, no matter how appropriate its use case, comprehensive its strategy, engaged its stakeholders, or demonstrable its value, the success of scaling still depends on one thing: integration.

The easier a solution is to integrate into existing infrastructure and workflows, the easier it is to scale. This depends on a number of factors, not least of which is the solution itself. But it also depends on a company’s broader innovation strategy and engaged stakeholders.

Over the next five blog posts, we’ll go into each of these steps in depth, providing real-world examples from successful rollouts. You’ll find that success builds upon success—each step follows the last and works because it worked. In the end, every successful rollout starts with success in mind. If you're eager to get started, schedule a demo now.

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© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

Do you want to implement AiSight’s predictive maintenance solution in your business? Great choice! But you may be wondering, what happens next?

Thus begins our onboarding process. This is a rewarding and streamlined process, during which we’ll learn everything we can about your current reality, advise you on what you need, train you on how to use our system, install our sensors, run a validation phase, and monitor the results. When it’s complete, you’ll have already reduced unplanned downtime and saved money.

The process starts with a call. This is where you’ll meet your greatest asset at AiSight: your customer success manager. They will be your personal contact and guide you through the entire onboarding process and beyond.

The Onboarding Call

On this call, you’ll discuss your goals with your customer success manager. This is more than a conversation about what you want from AiSight—this is a conversation about how things currently stand. The status quo is important; we want to know what works and what doesn’t work in your facility—your high-maintenance machines, your machines that have recently failed, your current maintenance practices, and how you’re currently tracking maintenance and downtime.

From there, we can start to set up key performance indicators. To complete a successful evaluation phase, we need to measure the outcome. Establishing a starting point is necessary to see the changes brought by implementing our system. And, with these measurements in hand, we can let you know what to expect from the validation phase.

Discussing your current setup is also key to determining the best use-cases for our solution. We want to deploy in places where you’re going to see maximum return on investment, fast. That means addressing existing pain points and monitoring high-maintenance machines.

To get a complete picture through validation, we recommend deploying at least 20 Aion sensors. In a recent case, we installed 40 Aions on gearboxes and belt drives throughout a line. These machine parts  are prone to misalignment and looseness, problems that lead to breakdowns if undetected. That makes them great candidates for the validation phase—and monitoring in general.

Preparation and Installation

Once we know where to best deploy our solution, we can begin preparation. We’ll ship the sensors and cabling. Our installation technicians will survey your facility to advise on the best mounting positions, then secure the power supply and connectivity for the sensors. If WiFi is not available, we can set up IOT gateways.

Training is also a part of the preparation phase. We want you to get the most out of our system, both in the validation phase and beyond. That’s why we provide training on how to use the dashboard, and advice on installing sensors. Ease of installation is a unique advantage of our system; once you begin rollout, your maintenance team may consider self-installation. In order to obtain accurate results right from the start, however, our experienced installation technicians will perform the initial installation and show your team how it is done.

With preparation completed, we only need a day to install our sensors.

Initial Analysis

The initial analysis begins as soon as our sensors come online. Once operating, our system’s AI trains itself to detect anomalies in your machines’ behavior. But the initial analysis provides additional depth of detection: it finds defects immediately. This saves the AI from normalizing unhealthy vibration patterns. It also means that our system begins delivering on day one.

During the initial analysis, the vibration experts on our data-science team will perform an in-depth analysis of the vibration patterns coming through the AiSight Dashboard. This will reveal any early-stage faults. As the validation phase continues, you’ll be able to watch the abnormal vibration patterns amplify as the problems worsen. If this process is allowed to continue, they’ll trigger an alert from the dashboard.

In a recent case, the initial analysis from our 40 sensors on gearboxes and belt drives revealed 7 early-stage faults, each either looseness or gearbox defects. Three weeks later, one of the sensors detected an increase in vibrations; the dashboard issued an alert. The plant’s maintenance team, forewarned of this outcome, was able to repair the machine during scheduled maintenance.

Continued Validation

After the initial analysis, the validation phase continues. Our sensors will monitor your equipment; our dashboard will generate results and issue alerts. To get a complete picture of machine health, we recommend a six-month validation phase. Sometimes the results make themselves known so quickly and emphatically that we can move on to rollout sooner.

Your AiSight customer success manager will be available at your convenience this entire time, and will check in every two to three weeks. Once the validation phase is completed, your customer success manager will compare the outcome of the validation phase to the information we gathered in the initial onboarding phase, generate KPIs, a time to ROI, and see how the results have aligned with your goals.

Wider rollout can begin whenever you’re ready. Any help you need with rollout or integration is available; your customer success manager will stay close through rollout, and continue to check in regularly. From there, the future without unplanned downtime is yours.

If you’d like to learn what happens next, check out our future articles on the rollout process: 5 Steps to Successfully Implement a Digitization Project. If you want to get started now, schedule a demo.

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

There is no great company without a great team! Working at AiSight is proof of it; having fun while working together is very important to us. And it’s not just us; studies confirm that employees are much more productive when they are in an environment where they feel relaxed and connected with their colleagues.

Better Together

A team that sets goals together stays together–and stays strong. In workplaces where employees don't even know their colleagues, they’ll never know what they are working on. That makes a space where people can only work independently and only think about their own priorities. The benefits of collaboration are lost in this environment.

Knowing what our team members are working on means we can set goals as a unit, unite behind higher priorities, and think together. It also makes the workplace a respectful place for everyone. When we feel supported by others on the team, we become stronger—not just as a unit, but individually.

All for One and One for All

At AiSight, we want all the benefits of teamwork. It works for us, and it should work for every team member too, which in turn works for us. It’s a positive feedback loop! To keep it rolling, we offer benefits with flexibility and personal well-being in mind.

Having a healthy mind means having a healthy life: doing sports, eating healthy food, and staying hydrated. We encourage our team by offering active-lifestyle options in our benefits pool, including Urban Sports Club and bikes, and we always offer healthy snacks in the office.

In support of a healthy work-life balance, we also make working from home an option. This flexibility means you can spend more time with your family, dog, or just around the house. We’ve found that this also results in improved employee performance.

Today, more than ever, taking care of our team is more than just clever and compassionate management. It’s a necessity. This goes back to the onset of the corona pandemic in early 2020.

The Great Resignation

The Great Resignation was a period of significant worker resignations in 2020 and 2021. Resignations by employees between the ages 30 and 45 (known as the Millennial generation) increased by over 20%. Previously, Generation Z (20-25 years) had the highest turnover rates, but during this period Millennials out-resigned their younger colleagues.

Why did this happen? Did it have something to do with quality of life at work? The causes are manifold and interrelated. Many people began to question their lifestyle at their workplace. In most companies, when corona hit, people were forced to step back and take a break from work. But some companies weren’t able to arrange remote work. People began to see a new reality of work-life balance emerge. They could spend more time with their families, or even working on their own projects.

Once people started quitting their jobs, they started to look at companies that really cared about their employees. There’s more to this than just working from home: these were workplaces where they could really interact with their colleagues, where they could feel comfortable exposing their ideas and receiving feedback, where everyone could improve themselves.

The New Normal

Today, job seekers have thousands of possibilities to choose from. Finding these candidates may not be so difficult, but every employer would be wise to understand that long-term retention is key.

As workers, our employers really matter to us. It’s important that they let us know that we’re all part of a team.  At AiSight, we take many measures to unite our team, including regular team events, to keep us united even as we enjoy the benefits of working from home. We also strive for a workplace that feels like home, with regular dog visitors, plus a soccer table, for moments when you need a little break to free your mind.

Does this sound like the kind of place you’d like to work? We’d love to hear from you! Take a look at our job openings here.

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

We hosted our latest webinar, Reducing Production Risks with Intelligent Sensors (Produktionsrisiken reduzieren mit intelligenter Sensorik) on December first. 64 participants from many fields and countries joined industry leaders Matthias Auf der Mauer, founder and CEO of AiSight, and Manuel Zimmermann, manager of Funk Beyond Insurance, to learn about the impact of predictive maintenance solutions like ours on risk management.

If you’d like to watch the webinar yourself (with English subtitles) you may do so here.

For your convenience, here are four key points.

1. The role of insurance is changing in an unpredictable world.

“Nobody actually wants the substitutions offered by insurers. We want uninterrupted production...”
-Manuel Zimmermann

Manuel opened the discussion with an explanation of how recent volatility has changed the role of insurance. The COVID-19 pandemic has provided an unexpected test of the resilience of our complex and integrated supply chains. They have been found wanting: from the lack of resilience in JIT, to the concentration of value in facilities that can’t work without functioning supply chains.

Nobody predicted this kind of broad, systemic breakdown. When things break outside the parameters of what we consider breakable, how do we evaluate risk? In an unpredictable world, the goal of insurance has to change—simply reducing insurance costs is not enough; we have to insure against the unpredictable. The only way we can do that is with sweeping damage-prevention strategies.

2. Sensors and automated systems have a long history in insurance. But this is different.

“We’re talking about technologies that are really part of the value-added process for businesses…"
-Manuel Zimmermann

Technology has long had its place in insurance. It’s impossible, for example, to insure factories without smoke detectors or sprinkler systems. Like predictive maintenance systems, these systems even employ sensors and a certain level of connectivity. But they aren’t the kind of thing a factory owner spends money on happily—they contribute nothing to productivity.

AiSight’s solution reduces risk and adds value. Companies that adopt this solution stand to save maintenance costs, while also improving productivity—it makes sense even beyond the benefits of damage reduction.

“...that’s what we do at Beyond Insurance.”
-Manuel Zimmermann

3. The wood-processing industry case.

“In six months we recognized 26 faults with 50 sensors... saved about 200000 Euro in total lost production... and increased expected productivity (of maintenance?) by 20%.”
-Matthias Auf der Mauer

Matthias provided a recent use case that supports Manuel’s claims. Deployed in a wood parts fabricator over a six month period, 50 Aion sensors detected 26 defects. Not only did this predictive intervention save the mill 200.000 Euros in lost productivity, it increased maintenance productivity by 20%. In a mill that runs 24/7, every hour of uptime counts.

Manuel brought this back around to a systematic look at how small parts of systems—applicably any and all industrial systems—when overlooked, can cause great risk. Overheating parts can cause fires. Failed ventilation systems can force building evacuations. It all adds up to loss—lost machines, lost productivity, lost value.

4. Oversight and clear parameters make insurance easier for everyone.

“...here, a measurable value delivers payment of claim; meaning insurance pays the moment a sensor reading exceeds a predefined value.”
-Manuel Zimmermann

Manuel explained the advantages of automated oversight with respect to parametric insurance payment. In short, an impartial sensor, providing constant oversight, presents the best-case scenario for both customer and insurer—even in the worst-case scenario.

Besides the value in risk reduction and improved productivity, when it comes down to actually claiming insurance, the customer will receive their payment according to clearly defined measurements, provided by the sensor. The insurer, meanwhile, saves resources by automating the adjustment process. It’s a true win-win situation.

A Partnership?

If it sounds like AiSight and Funk Beyond Insurance should start working together, don’t worry—we are. Stay tuned; we’ll share everything you want to know about our new partnership in one of our next blog posts.

If you're interested in our solution schedule a demo.

Since you’re reading this, there’s a good chance you’re interested in working at AiSight. You’re probably also curious about the process of finding work at AiSight. What do you need to apply at AiSight? How long does it take to get hired at AiSight?

You want to put your best foot forward. And so do we. That’s why we’ve asked our HR Manager, Frances Völkel, to offer her guidance on the process of successfully applying to work at AiSight. It’s a straightforward, five-step process. It starts with you finding the position that works for you.

See, there’s a good chance we’re interested in you working at AiSight too. We’re growing. By the end of 2022, we plan to employ 100 people—more than triple our current numbers!

That means we’re in the midst of a serious hiring spree. We’re currently hiring for all positions—you can find them all here. And we especially need staff in sales, software development, and customer success.

If you don’t see your role listed but still want to join the team, why not apply anyway? Above all, we’re looking for team members who are open, adaptable, versatile, ready to work in a dynamic environment, and looking to grow with us. If that’s you, we might have just the job for you. Simply fill out our online application form and send along your CV.

That’s All it Takes to Get Started

Really! We love getting motivation letters but they’re by no means mandatory. Your CV and one short form with seven fields is all it takes. You can even upload your CV within the form.

Of course, you’ll want to make sure your CV is error free and tailored to your position. If you’re applying for a creative position, go ahead and include your portfolio. We’ll screen your CV and get back to you to schedule the second step.

Make a great first impression! Your CV should be on point and well structured. How you present yourself matters too. You shouldn’t pretend, just be who you are. -HR Manager Frances Völkel

The Intro Call

Our next step is to schedule a 30-45 minute call. You’ll get to meet someone from the HR Team and discuss your CV, and professional and educational history.

This is also our chance to introduce you to AiSight. We’ll discuss the tasks you’d take on, the team, and our plan for the next year. Of course, we also want to show you that this is a great place to work! From team events, to benefits, to company culture, we have a lot to offer. If there’s anything you need to know about working at AiSight, this is your first opportunity to find out.

With our relationship established, we can move on to the third step.

The Case Study

The best way for all of us to determine whether you can work at AiSight is to get you to work! This is the single biggest stage of the process: the hiring project—your chance to really show us what you can do.

This will be a real-life task; the kind of work you’ll take on when you join the team. Applying for a position in operations? We’ll give you tasks and questions concerning communication with suppliers, handling stock, and principles of project management. Software? We have coding challenges for you. Sales? Strategic questions and sample pitches await.

You’ll have five to seven days to complete and submit your work. We’ll then schedule a presentation with the relevant team leader. Ideally, we’d love to meet in person, but whenever that’s not possible we can arrange remote meetings. Your presentation will be 15-20 minutes of a one hour meeting. We’ll spend the rest of the time discussing your project, and you’ll have the chance to ask questions about the work.

When we’re sold on your skills, it’s time to move on to the fourth step!

Take Me to Your Leaders

We like to follow the work project with two or three more calls or meetings. Again, ideally we like to meet at least once in person, but whenever that isn’t possible we can meet remotely.

This is our chance to get to know you a little better—and you us. You’ll get to meet the founders and other key players, deepen your feel for company culture, attach faces to names, start connecting with the team, and discover everything else you need to know about AiSight to come aboard. By this point, you’ll probably have a bunch of new questions. Feel free to ask!

And that’s it. On the fifth step you’re hired!

So how long does this all take?

We want to move things along as quickly as possible—we have work to do and people to hire! Of course, things don’t always go to plan. But we aim to get every applicant through the process in three to four weeks. The longest single step of the process is the hiring project—step three. We give one week time for you to do the task with no stress.

Finally, now that you know how to apply, why not take a look at what’s waiting for you as an AiSight team member? Benefits. Team Events.

Now that you know what to expect, why not take a look at our openings? We’re hiring for every position. We’re looking forward to hearing from you!

© 2022 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

At AiSight it’s important that we regularly strengthen our team’s motivation and cohesion. At the same time, we want to encourage exchanges outside of work to ensure a better and more pleasant working atmosphere.

What could be better suited to this than team events?!

In 2021, we’ve already held a lot of great team events. At the beginning of the year these were only remote events, but towards summer we were able to spend more and more time together in real life, besides work.

Of course, we have also adhered to the country-specific Corona guidelines here.

To give you an idea of what we’ve already done, here’s a brief review of our past events:

February 2021: Solve the Mystery Escape Room

Engineers by day, archaeologists by night. In February, we attended a virtual escape room and worked as a team to solve a mystery! Our goal was to find the true origin of the cursed skull and return it before it was too late!
Spoiler: Of course we made it. ;)

March 2021: Online Games Night

Our game-based, team-building events continued: In March we had a virtual game night, starting with a game of Scattergories, then a Pixel Recreation Challenge!

In Scattergories, a random letter is picked and you have to fill predefined categories with words starting with the picked letter. In the second game, we had to recreate an image based on a color-formatted spreadsheet. And what could be better as a template than a unicorn? This really challenged our inner artists!

April 2021: Online Games Night 2.0

You can already guess what we did in April? Right—we got online-game-night fever. Of course it turned into another evening with virtual games.

This time we played Gartic Phone (aka the Telephone Game or Stille Post), but instead of just whispering what we understood, we had to draw a sentence someone else wrote and then interpret other people's drawings. What a fun night!

May 2021: 'no Spain no Game' The Fabulous Game!

Game Night!!! Nothing new to you, we know. But this time organized externally, and with a slight learning curve. We played a virtual game called "No Spain no Game", in which we had to do some scavenger hunts, answer some true-or-false and trivia questions, and we even had to dress up a bit for some photo challenges.

At the same time we got to learn a lot about Barcelona, Spain in general, in a very fun way.

June 2021: Finally. A Personal Get-together Again

After months of communicating almost exclusively via the screen (some of us hadn't had a chance to meet some of the teammates at all), we met again, in real life, for the first time, in June. We went to the Holzmarkt Berlin, where we toasted our team and the get-together, and ate dinner together. There is nothing better than spending an evening with beer, pizza, and great colleagues..

July 2021: Cooking Party

In our July team event, we met up for an Asian-food-themed night. We cooked dumplings, summer rolls, and other delicious asian specialties. (Thank you to our BizDev Manager Marcela for hosting this in your awesome kitchen.) We were all amazed at how many great chefs there are among our colleagues.

August 2021: Artnight “Sommer, Sonne, Kaktus”

We have always thought that there were some hidden artistic skills in the AiSight team, but no one expected this. In August, we hosted the "Artnight" workshop by Realtainment, in our office. Each team member was provided with a canvas and some colors. Under the guidance of an instructor, they created wonderful paintings under the theme "Sommer Sonne Kaktus" (or Space Plants, as we called it :D).

September 2021: Partytime!!

In September, AiSight turned 3 years old. To celebrate, our September event was a big birthday party. Everything that belongs at an incredibly cool party was there: a photo box with props, a dance floor with 3 DJs, a huge cake, a great buffet and drinks, a chill-out area with a tattoo and glitter station, and much more.

The year is slowly coming to an end, but we still have great ideas and plans in store for how to spend a great time together over the next few months.

Stay tuned for a photo walk, our Christmas party 2021, and many other great events.

Follow us on Linkedin, Facebook, and Twitter to stay informed on our latest events.

And by the way: We are hiring! So if you want to be part of our next team event, take a look at our open positions and apply 👇🏻

© 2021 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de

What is Firmware?

Put simply, if hardware is what you touch and software is what you virtually interact with, firmware is the software responsible for telling the hardware what to do. In other words, it’s the software for devices that are not conventional computers.

You’re probably wondering whether we ever interact with firmware in our daily lives. The answer is yes. When our headphones, or any other devices, are not working, our last resort is to perform an update. That’s when we interact with firmware.

“Well... If you tried everything, updating is your last resource”

Davi Herculano, our Firmware Developer

How does Firmware work?

As we explained, firmware are programs for devices that are not computers. Almost every device with elaborate working logic uses firmware, including keyboards, microwaves, TVs etc. But how exactly does firmware tell them what to do? It’s easiest to explain allegorically. Think of firmware and its related elements as follows:

Computer: a super efficient employee

Firmware: a task list

Compilers: software that translates the task list into the employee’s language

Peripherals: the employee’s helpers who interact with the external world

So, the computer is a very efficient employee: they have limited short-term memory (cache), but they use a notebook (RAM) in which they’ve recorded their task list. The task list, in this case, is a simple program. The only thing to make sure is that the tasks are written in a language that the employee can understand. But remember that this employee is a computer—it has its own set of possible instructions, making it possible to transform every instruction into 0s and 1s. Translating all instructions into every employee’s language would require learning all of their languages. That’s why we use compilers: to translate our firmware (task list) into hardware (employee) language.

Next, we want to understand how the employee actually performs their tasks. Computers have the following components:

• Program memory: where the task list is stored.
• CPU: employee’s calculation capability
• RAM: the employee’s notebook.
• Counter: tracks which task list item the employee is working on
• Internal oscillator: defines the time interval scheduled for each task
  

To perform each task, the employee actually needs to interact with the outside world. For that he has several helpers, known as the peripherals. Peripherals are pieces of hardware that perform specific tasks (communication, count time, access memory). They live inside the Integrated Circuit and can have control over the microcontroller pins.

The employee, in turn, writes task lists for each of the helpers. Each helper can then control the pins to alternate tasks very quickly and send/receive messages to/from other devices. This is how the software and hardware come together to make the magic happen.

Wrapping up

• The computer is like an efficient employee who can read, write, and do calculations.
• This employee has a task list and follows it exactly.
• Programmers use compilers to transform code into task lists.
• Peripherals do the magic of interacting with the real world. The employee sends instructions so they can perform different tasks.

Aion

We’ve frequently discussed how our predictive machine maintenance solution includes both hardware and software elements. Our software provides the high-quality analysis you can depend on to predict machine-maintenance issues. Our hardware feeds our algorithms accurate and reliable data. Finally, the firmware ensures that our Aion hardware knows what to do when plugged into industrial machines. Are you looking for a Predictive Maintenance solution? Request a demo now!

© 2021 AiSight GmbH. All rights reserved

Phone: +49 (0) 30 40363399

Website: https://aisight.de