A study by the German Academy of Science and Engineering, known as Acatech, provides the most sophisticated blueprint yet for smart manufacturing, and a methodology for companies to rate their industrial transformation.
Acatech’s Industrie 4.0 Maturity Index was written for manufacturing companies, specifically, but its theory can be applied to any corporation in any field, which is seeking to set about digital transformation. Its crucial point is the process of transformation is evolutionary, taking several years, and requires changes across large parts of organisations. The most difficult of these changes are cultural, it notes.
The maturity index is the work of a collaboration between research institutions and industrial enterprises, including a notable contingent from industrial transformation agent PTC. The study sets out a methodology for companies to gauge their own progress towards digital transformation, and proposes strategies for them to complete the journey.
Its framework divides the internal aspects of a company into corporate structure, corporate processes and corporate development. Im essence, it proposes a self-assessment model for digital maturity based on how a company’s structures and processes rate for digital development.
It defines six fundamental development stages, which signpost the way ahead, like staging posts on a digital roadmap. They start with two digitalisation phases, computerisation and connectivity. These are the basic requirements for more sophisticated digital working; they are followed by four additional stages to achieve digital maturity.
Capabilities should be built incrementally, it notes; the benefits of earlier stages can be achieved with fewer capabilities. Companies can use these development stages to plot a course, and rate progress for every corporate structure and process.
The model breaks a company’s structure down into four areas, indispensable for the production of goods and services. These are resources, information systems, culture and organisational structure. It also considers five corporate processes, or functional areas, which businesses rely upon to get work done. These are development, production, logistics, services, and marketing and sales.
The below diagram shows inter-lays this four-tier corporate structure and six-part digital development. Companies must consider these development stages, depicted as six concentric circles, in the context of both their structural and functional areas to ascertain their real digital maturity, and formulate a plan of attack.
Below, we consider the six development stages, handing the story telling over to Acatech itself.
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DEVELOPMENT STAGE 1 | COMPUTERISATION
“The first stage in the development path is computerisation, since this provides the basis for digitalisation. In this stage, different information technologies are used in isolation from each other within the company.
“Computerisation is already well advanced in most companies and is primarily used to perform repetitive tasks more efficiently. Computerisation delivers important benefits by enabling cheaper manufacturing to higher standards and with a degree of precision without which it would be impossible to make many modern products.
“Nevertheless, it is still possible to find many machines without a digital interface. This is especially true of machinery with long cycles or machines that are manually operated. In these cases, terminals are often used to provide the missing link between business applications and machines.”
DEVELOPMENT STAGE 2 | CONNECTIVITY
“In the connectivity stage, the isolated deployment of information technology is replaced by connected components. Widely used business applications are all connected to each other and mirror the company’s core business processes… but full integration of IT and OT layers has not yet occurred.
“IP is more and more widely used, even on the shop floor. Connectivity allows design data to pushed to production, and confirmation of manufacturing can be provided in real time via an MES system. It also allows machine tool manufacturers to perform remote maintenance on products being used by their customers thanks to the availability of cheap, high-volume data links.
“In existing factories, assets are kept in production for as long as they continue to produce quality products. Since IP enables standardised communication on the shop floor, new sensor technology means these assets, which remain productive, can easily be connected.”
DEVELOPMENT STAGE 3 | VISIBILITY
“Falling sensor, microchip and network technology prices mean events and states can now be recorded in real-time throughout the entire company and beyond rather than just in manufacturing cells. This makes it possible to keep an up-to-date digital model of factories at all times.
“This digital shadow can show what is happening in the company at any given moment so that management decisions can be based on real data. It is thus a core building block for the later stages. [But] producing a digital shadow is a major challenge for many companies.
“Data is often held in silos. For functions like production, logistics and services, very little data is collected at all. In addition, wider use of data is often prohibited by system boundaries. To achieve the goal of an agile learning enterprise, comprehensive data capture right across the company is essential.”
DEVELOPMENT STAGE 4 | TRANSPARENCY
“To identify and interpret interactions in the digital shadow, captured data must be analysed by applying engineering knowledge. The semantic linking of data to create and contextualise information allows for complex decision-making.
“Big data applications, typically deployed in parallel to ERP or MES systems, provide a common platform that can be used to carry out extensive stochastic data analysis to reveal interactions in the company’s digital shadow. This transparency can for example be used to carry out condition monitoring of machinery and equipment.
“Recorded parameters are searched for mutual events and dependencies that are then aggregated to produce complex events reflecting the condition of the machine or equipment. Among other things, transparency is therefore a requirement for predictive maintenance.”
DEVELOPMENT STAGE 5 | PREDICTABILITY
“This involves projecting the digital shadow into the future in order to depict a variety of scenarios. As a result, companies are able to anticipate future developments so that they can take decisions and implement the appropriate measures.
“While measures still have to be carried out manually, longer lead times help to limit negative impacts. Reducing the number of unexpected events enables more robust operation of the business. It makes it possible to flag up recurring logistics issues before they even occur.
“A company’s predictive capacity is heavily dependent on the groundwork it has previously undertaken. A properly constructed digital shadow combined with a knowledge of the relevant interactions will ensure both forecasts and recommendations are of a high standard.”
DEVELOPMENT STAGE 6 | ADAPTABILITY
“Continuous adaptation allows a company to delegate certain decisions to IT systems so it adapts to a changing business environment. The degree of adaptability depends on the complexity of the decisions and the cost-benefit ratio.
“The fundamental feasibility of performing repeatable operations autonomously should be investigated. It is important to assess the risks of automating approvals and acknowledgements for customers and suppliers carefully. Examples include changing the sequence of planned orders because of expected machine failures or to avoid delivery delays.
“The goal of adaptability has been achieved when a company is able to use the data from the digital shadow to make decisions that have the best possible results in the shortest possible time and to implement the corresponding measures automatically, without human assistance.”
