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Much ink has been spilled about Industry 4.0.  The promise of Digitalization, Big Data, Automation and 3D Print are expected to fundamentally transform the production and delivery of goods.

Each of the preceding Industrial Revolutions resulted in unexpected social and economic change: colonialization, wars, urbanization, population growth and even life expectancies, can all be traced back to industrial revolutions.

American socialist, Robert K. Merton popularized the concept of unintended or unforeseen consequences.  Although the Fourth Industrial Revolution is still in its nascency, far-reaching consequences are likely.  In this article, I will explore three of the unintended or unforeseen consequences of Industry 4.0 and the social, environmental and business impact.

Operational Health and Safety

Industrial IoT Predictive maintenance can address two significant contributors to work-related injuries.

First, unplanned or reactive maintenance is the cause of workplace injury. When machinery stops unexpectedly, there is pressure on work crews to restore production and fix the immediate problem. Without the benefit of Root Cause Analysis (RCA), O&M workers often resort to trial-and-error.  Unfortunately, these activities sometimes lead to risk-taking and ultimately injury.

A second factor is the aging industrial machinery in developed economies such as the United States. When industrial assets are used beyond their intended life design, they add additional burdens to O&M professionals as failure rates increase and additional maintenance is required.

In the Bathtub Curve depicted below, it is shown how maintenance increases as assets age and wear out failures increase.

industrial analytics

How does IIoT for Predictive Maintenance reduce potential workplace injury?  IIoT Predictive Maintenance applies Artificial Intelligence Machine Learning Algorithms to the sensor data generated by industrial plants.  These algorithms are looking for anomalous behavioral patterns and use it to identify evolving signs of asset degradation.  By correlating anomalous patterns, the root cause of an upcoming failure can be identified, and technicians can remediate before downtime occurs.  This gives technicians extra time and detailed information, thereby reducing both the pressure and guesswork.

Although still in its inception, automated robotics-assisted repairs and drone inspections, are likely to further reduce injury rates.

The impact is significant.  In the Oil & Gas industry alone, the World Economic Forum is predicting that Industry 4.0 and digitalization will lead to a 3% reduction in workplace injuries.

The Environmental

The first two industrial revolutions had negative long-term environmental and ecological consequences.  The use of fossil fuels, the disposal of industrial waste and the byproducts of production have polluted air and water.

To what extent does Industry 4.0 impact the environment? It should be remembered that factors such as public policy and multilateral agreements are critical considerations and it is too early to predict whether Industry 4.0 can contribute to a reversal of climate change.

At the same time, there are examples of long-lasting environmental damage caused by preventable disasters.  The BP oil spill of 2010 is considered the largest marine oil spill in the history. According to a federal investigation, a last-ditch safety device on the underwater well had multiple failures and was not tested properly.   Catastrophic events extend beyond the Oil & Gas industry. In the US alone, there are about 150 environmental disasters recorded annually.

Because IIoT Predictive Maintenance provides industrial plant technicians with alerts of evolving failure, they can fix a specific problem before the asset stops functioning. Today, in the absence of accurate failure alerts, industrial plants engage in preventive maintenance.  According to one study, 40% of preventive maintenance costs show negligible results and 30% are carried out too frequently.

Another potential cause for disaster stems from the reliance on visual inspections. Because visually inspections are manually performed they are prone to human error.  Furthermore, human inspections do not provide a comprehensive view of all machinery.  Industrial assets in remote locations or simply difficult to reach may not be consistently inspected.

It is likely that Industry 4.0 will shift away from costly, error-prone and often redundant manual maintenance activities.  The corollary result is a reduction in environmentally harmful accidents.

Vendors’ Business Models

Industrial plants increasingly view the digitalization of machinery and equipment as a corporate priority.  As Industry 4.0 gains traction, one could argue that Big Data is the new oil of the 21st century.  The logic is that whereas oil fuels the physical factory, Big Data fuels the digital factory.

Although there are limitations to this comparison, the importance of Big Data should not be underestimated. Today, many of the traditional Original Equipment Manufacturers (OEM’s) that manufacture industrial equipment are watching the dawn of the Fourth Industrial era from the sidelines. We expect this to change.

Embedded within industrial machinery are sensors that generate operational data. We believe that inevitably many of these OEM’s will provide tools to analyze the Big Data generated by their machinery and provide real-time indicators of asset health performance. OEM’ that bundle IIoT Predictive Maintenance service with their hardware will be able to change their pricing models.  One option is Hardware as a Service or HaaS.

What does this mean for the industrial plant?    We expect to see various flavors of HaaS emerge.  The most likely common scenario is that instead of charging for equipment upfront, payments will be made over the lifetime of a service agreement.  From an accounting perspective, this means the opportunity for industrial plants to replace Capex with Opex and to reduce the reporting of assets and liabilities on the balance sheet.

Summary and Conclusion

The First Industrial Revolution gave rise to economic principles and social movements with multi-generational consequences.   These include the birth of movements ranging from capitalism to Marxism.

With Industry 4.0, changes are likely to occur in areas that we are unable to predict.  It is logical to expect the creation of new value models and the redistribution of some existing wealth.  At the same time, if Industry 4.0 lives up to its potential for production efficiencies, this will benefit both mankind and our planet.

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Avi Nowitz

Avi Nowitz

Avi Nowitz writes about the financial impact of Machine Learning on the industrial sector. Avi started his career on Wall Street as an equity analyst, providing institutional investor research on manufacturing companies. After completing his MBA in Finance from New York University, he joined the consulting division of Peppers and Rogers Group where his international clients included Bertelsmann, Ford Motor Company and Doğuş Holdings. For more than a decade, Avi led the Microsoft Consulting Practice at New Age Media and managed the execution of initiatives in EMEA and APAC.