The Value of Looking at the Big Picture

A company’s system landscape is traditionally heterogeneous. There is sometimes a colourful variety of software systems being used and these systems aren’t always networked with one an-other. On top of this, different engineering departments – for instance, electrical engineering and mechanical engineering – often still work on stand-alone solutions, remaining isolated from each other. Another point of weakness is communication exchange; many companies are still using paper printouts instead of going digital. The more unstructured and decentralized the documentation and availability of product and plant system data, the more time each and every work step consumes. However, those who wish to generate new gains in efficiency should be focusing on the processes. The greatest potential isn’t to be found hidden in software solutions, but in the process. The interaction of all the systems – from planning to engineering to manufacturing – is the key to more value creation. Simply looking at the purely technical infrastructure falls far short of what is needed.

The systems of the future can and must communicate with one another. With respect to machine and plant system engineering, a number of basic prerequisites are necessary. First and foremost is product data. Such data includes device data for a machine or plant system that must be one hundred per cent digital. The data requires a logical structure and comprehensive technical specifications so that the information can later be taken from the CAx system and used in mechanical production, for instance for drilling patterns on control cabinets or for controlling NC machines or automatic wire assembly modules.

Increasingly Important: The Digital Twin

The digital twin is no less relevant in this discussion. It is necessary to implement digital engineering and design based on the digital twin so that the theoretical design will work in practice. Reducing latency times by means of interdisciplinary and consistent use of a digital twin is a promising approach for significantly accelerating engineering and production processes and for reducing costs over the long term. In the segments of design/development and production, the data, analysis and decision latencies have the greatest efficiency potentials. The goal is to drastically reduce both the required time and the incurred costs while simultaneously increasing the quality of the measures implemented. A comparison of analog and digital strategies outlines the considerable potential. If design/development and production are carried out conventionally – meaning successively, reactively and primarily using paper-based and/or individual knowledge, all reviews, analyses and decisions on measures to be undertaken can only take place in sequential order.
The digital alternative to working with paper consistently networks data and processes for strategic planning, development, documentation and manufacturing. Processes can be accelerated if real-time data is available for a digital twin by interlinking information flows and industry-specific software. A collaborative development environment is the prerequisite for going from a digital prototype to the creation of complete manufacturing documentation.

Showcase scenarios in augmented reality are already showing the way: sensor data is being compared and simulations are being successfully carried out so that machine downtimes can be prevented from the outset and maintenance can be carried out preventively.

Trend Factors: Machine Learning and AI

Machine learning and artificial intelligence (AI) are key trends in digitisation. One hundred per cent digital data is a prerequisite here as well. Numerous scenarios in augmented reality and AI are already showing the way: sensor data is being compared and simulations are being successfully carried out so that machine downtimes can be prevented from the outset and maintenance can be carried out preventively. For instance, a drive control system is consuming too much energy. A trend can be calculated based on loading scenarios for the machine and the drive unit can be better designed. This provides companies with an important basic guide for designs to optimise operating costs. This is where software tools and methods play an ideal role.

How Software and Methods Interact

It’s precisely this interaction between software and methods that accounts for long-term success. What systems are already learning step by step – improved, direct communication in the sense of continuous and integrated data exchange based on a single source of truth also applies to project participants to the same extent. Development, design and manufacturing must work together interactively. Walls preventing communication between departments must be demolished. This requires change management, ideally driven and pushed by upper management. In many cases, professional consulting can also be a means to this end. After all, many company processes have already been learned and are considered unchangeable. An outsider view can help in recognising potential and in breaking through existing patterns of thinking.

An outsider view can help in recognising potential and in breaking through existing patterns of thinking in the sense of change management. Professional consulting can be productive in achieving this.

Trend Platform Economy

Another trend as part of digitisation is the move towards platforms and ecosystems that will be functioning as marketplaces in the future. Machine and plant system manufacturers are facing particular challenges in this arena because these future marketplaces are vertically structured platforms in competition with one another. Partner networks offer the possibility to enjoy joint success across industries. Connectivity and interoperability are crucial to success. This originally technical perspective can also be applied to people. Establishing one’s own (partner) networks and participating in others promotes cooperation and openness for joint innovations. The networking of machines starts with the networking of people.

Conclusion

The greatest potential isn’t hidden in the choice of software, but instead in the overview of the entire process. The prerequisite for optimal value creation is one hundred per cent digital data as the foundation for integrated development and manufacturing. The digital twin is the “enabler” for this interaction of systems – from planning to engineering to manufacturing. Intelligent structuring of processes and data as well as that of teams and corporate structures ensures long-term company success. EPLAN, as an integrated solutions provider, supports companies on their paths to exploiting potential efficiencies in engineering with a wide array of service and consulting offerings in the era of digitization.