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Finding success with smart factories can be a frustrating experience. It’s not for lack of trying, since most major companies have undertaken projects, but as a Cap Gemini report shows, it appears they are not getting the results they’d expected.

How can we rescue Industry 4.0 (I4.0) from failure? More than just new technology, it requires getting back to basics.

Industry 4.0 Background

The Industrie 4.0 Working Group presented concrete recommendations to German Chancellor Angela Merkel at the Hannover Messe in 2013. It anticipated that applying internet-of-things (IoT) devices in manufacturing would allow businesses to establish global networks by encompassing products, equipment, transportation, storage systems and more. It calls these cyber-physical systems (CPSs) — physical entities with augmented capabilities provided by electronics, including sensorization, communication and computerization. These CPSs, known as smart entities, would be capable of autonomously exchanging information, triggering actions and controlling each other independently.

CPSs are vertically networked with the factory business processes and horizontally connected to the entire supply chain. This smart ecosystem would allow the real trigger for the I4.0: consumers’ desire for truly one-off products that match their unique requirements and tastes for the price of a standard product.

Long gone are the days of the Ford Model-T available in “any color … as long as it’s black.” Custom products can now be made profitably thanks to the extreme flexibility of such smart manufacturing and supply chain networks.

Industry 4.0 Efforts Underway

Amid the excitement of such promises, new technologies have been applied in manufacturing environments at a high pace, including IoT platforms, big data, machine learning and augmented reality, among others. However, the companies that have implemented these technologies have lacked an overall digital transformation strategy. Lots of dispersed solutions were applied to suboptimized factories without the required maturity.

So it comes as no surprise that despite the investments, most companies did not achieve what they wanted. According to the aforementioned Cap Gemini report, although 68% of the 1,000-plus manufacturers with revenues above $1 billion reported having ongoing smart manufacturing initiatives, so far only 14% call them a success. So, why aren’t the huge investments paying off?

Back to Basics

In the midst of the excitement, some very important aspects seem to have been forgotten.

• Strategy: Start with the end in mind. I4.0 requires nothing less than a holistic, mid- to long-term digitalization strategy. And it must spring naturally from the business strategy.

The best digital strategies aspire to disrupt the value creation. Like BCG says, “Digital strategies fail more often because of too little ambition rather than too much.”

• MES: Organize shop-floor processes. To implement such a strategy, the improvement initiatives need to both collect information at the right level of granularity and control the manufacturing processes. At the shop floor, there’s only one class of software applications that has been designed to do that: manufacturing execution systems (MES).

These systems have been designed to become the backbone software for shop-floor operations, around which all other applications operate. Without such a backbone, the digitalization initiatives create dispersed and siloed solutions, with two consequences: The data collected does not have the right contextual information to unleash all the improvement potential, and dispersed solutions cannot control processes because these span across areas, people, physical and business entities.

A strategic approach should then start with a manufacturing-wide solution, mapping processes and enabling their control and improvement, enhanced by all other I4.0 technologies.

• No shortcuts: ‘Rome wasn’t built in a day.’ The fact that so many manufacturers believe they’ll see the benefits from their investments — without considering strategy and plant organizing approaches — may indicate a lack of digital maturity.

There are several maturity models for manufacturing, but one in particular, from acatech, has been created with a systematic approach to I4.0, helping companies determine the stage they’re currently at and identify the required measures to achieve higher levels.

The model encompasses six stages, starting with computerization with isolated systems, which are then replaced by connected components in stage two. Subsequently, visibility, transparency, predictive capacity and adaptability stages complete the model.

I4.0 starts with the third stage, where data collected across the entire plant is combined with PLM, ERP and MES systems to create full visibility. This step seems to be what’s missing in many digital initiatives, as 62% of companies surveyed reported having no MES in place.

• Improved: The way we’ve always done it may not be good enough. MES has always been a key element in manufacturing continuous improvement, by collecting data at the right level and becoming the main source for the programs. Then, once the program reaches its conclusions, it is at the MES that the improvement changes need to be implemented, automated and, ultimately, controlled.

Like MESA puts it, although Lean manufacturing techniques have existed for many years, it is only with state-of-the-art MES that manufacturers can fully realize their benefits, sustaining and scaling a lean enterprise.

Industry 4.0-ready: a New Generation of MES

I4.0 manifests itself in a variety of pressure points: an increase in the number of concurrent products, smaller batch sizes, tighter tolerances, increased traceability requirements, intense cost pressures and shorter time-to-market windows.

In this environment, the cycle (control – analysis – improvement – changed model) needs to happen at an unprecedented speed — so fast that the MES model supporting it must be incredibly easy to change, while new levels of automation must feed and control the model. The data for analysis and improvements must be available unfiltered and quickly to data scientists and machine learning algorithms.

The objective is then for manufacturers to become agile learning organizations, making better and faster decisions to continually adapt themselves. And, in a nutshell, this is why a legacy MES won’t be enough.

Rescuing manufacturer’s I4.0 initiatives from failure requires coming back to the basics of strategy, step-by-step improvement and ways to collect data for effective process controls, leveraged by modern MES, which shall be the backbone of Industry 4.0.