As an expert on process data, the Kistler Group is focusing intensive efforts on offering its customers digital services that deliver added value – ranging from individual assembly processes to the entire production environment. The emphasis is increasingly on one objective: holistic optimization, from sensor and machine level all the way through to post-processing.
The digitalization of industry is in full swing. As information and operation technology become more closely merged, there is greater potential for boosting efficiency in production. Kistler is working at many different levels to support production companies with intelligent services for the digital value chain. This process is increasingly driven by software. Key factors here include universal data consistency and networking, the digital twin at process level, platform-independent transparency and traceability, and cause-oriented analysis of big measurement data.
Comprehensive connectivity is the basis
To advance towards the vision of fully networked industry – as denoted by the term "Industrial Internet of Things" – Kistler aims to achieve maximum connectivity and data consistency. This includes open, machine-independent interfaces and protocols such as OPC UA, as well as the maximum possible level of compatibility on the shop floor. Much of the production plant that is already installed dates back many years, but it needs to be integrated just as much as the latest machinery equipped with Euromap 77.
Kistler is taking another step in this direction by collaborating with one of the leading companies in the Manufacturing Execution Systems (MES) sector. This partnership aims to bridge the gaps between the machine-based process level and the higher-level process control systems, with data made available on a cross-platform basis. In the future, additional collaboration partnerships with providers of production control systems will help to complete the cyber-physical system architecture for a fully networked production environment.
This involves far more than the smooth and efficient integration of leading process monitoring systems such as ComoNeo (for injection molding) or maXYmos (for all steps in the assembly process). The objective is to make all data at process level – for every single step in manufacturing a product – available in real time, and to assign the data to the relevant work orders or products (digital twinning). This is actually a fundamental requirement for highly regulated industries such as automotive engineering and the medical or pharmaceutical sectors. This approach very rapidly generates huge volumes of measurement data that require efficient management and evaluation – so suitable software to analyze big data is essential.
From digital twin to intelligent production
One of the critical links in the digital value chain is the digital twin for every single manufactured product. Which machines and devices were involved? Which tool, mold and/or recipe settings and parameters were used, and what were the ambient conditions? Which processing or machining steps were performed, and what were the results? How can the resultant quality be assessed and visualized in detail? Increased availability of reliable information is the key to targeted optimization of production – especially in view of developments such as smart factories with integrated control and the possibilities for individualization required for Industry 4.0, with the trend towards batch sizes of one.
In the future, Kistler's customers will enjoy the added benefit of new digital services that offer application-oriented measurement technology based on usage (information-as-a-service):
- Device management: efficient management of equipment and interfaces – maximum standardization, tried-and-tested UX design
- Distributed numeric control (DNC): providing, distributing and versioning recipe and tool parameters – reduced setup costs, recipe analysis, increased process monitoring
- Visualization and control: platform-independent, individual or user-specific visualization of all process information – complete overview of production progress and overarching process control
- Traceability: allocation of order and process data, accurate to the individual part – full documentation, troubleshooting and end-to-end traceability
- Data analytics: recognition of patterns in large data volumes and machine learning – enhanced problem-solving capabilities, less machine downtime, higher OEE
Overarching convergence and visualization of data related to processes, machines and the environment: this is a challenging objective that should not be underestimated. The goal: to provide different users – from shop floor to management – with the relevant information as a dashboard on any desired terminal device. To achieve this, Kistler is investing heavily in web-based technologies and related expertise. This is the only way to develop extended potential for usage and control while meeting current expectations for usability and safety. The ultimate objective is to develop self-managing machines and processes that pave the way to predictive and predictable production.
Generating new knowledge to optimize manufacturing
Big measurement data and data analytics open up yet more possibilities that have an equally critical part to play. In these fields, organic growth coupled with a series of acquisitions have given the Kistler Group know-how that it can already pass on to its customers. Successful analysis of huge volumes of process data requires software expertise that is specifically geared to measurement data; standard algorithms are often unable to cope with analyses of this sort. Application-specific solutions for individual activities such as plastics processing, assembly monitoring and fastening technology make it possible to identify new relationships – thanks to pattern recognition and machine learning, even on a long-term basis. Trend or curve analyses and testing hypotheses when bad parts occur: these are the tools that are raising process optimization to a new level.
As a leading manufacturer of piezoelectric measurement technology, Kistler is also implementing these new systems in its own production facilities. This creates a win-win situation: by improving our own processes, we can also improve product quality – and at the same time, we can test the solutions we develop not only in the laboratory but also under real conditions.
Kistler already has the means at its disposal to press ahead with digitalizing production, and it will go on expanding these resources in the future – not least with the help of strategic cooperation alliances to develop software and industrial applications. The focus now is not only on systems and solutions, but also on information and services that help customers to achieve sustainable, holistic improvements to their production processes. The combination of Kistler's expertise in measurement and analytics with its development partners' production and application know-how creates the ideal basis for developing customer-centric solutions and services. In this way, the measurement chain is being transformed into the digital value chain, integrating additional intelligence into machinery and plant – all the way down to each individual processing step, and across all functions and levels. The goal of Industry 4.0 is the largely autonomous factory that controls itself – and with these developments, that goal is close to becoming a tangible reality.