processes Digital
processes Digital transformation is changing the cutting tool manufacturing industry by Thomas Götz, Andreas Gebhardt and Dr. Marco Schneider, Fraunhofer Institute for Manufacturing Engineering and Automation The Digital Transformation within economy and society is from today’s point of view seen as the 4th Industrial Revolution (figure 1). Worldwide manufacturing companies must evaluate the new digital technologies with respect to their business model and competitors. In particular the small and medium-sized enterprises within the cutting tool manufacturing market lack a precise concept, which steps need to be taken for the implementation of digital technologies and which efforts and benefits can be expected. The Fraunhofer Institute for Manufacturing Engineering and Automation IPA in Stuttgart developed a technology roadmap for small and medium-sized enterprises in the tool manufacturing market in Germany within a funded project by the Federal Ministry of Education and Research “Innovationsforum Zerspanwerkzeuge”. The results were presented at the International exhibition for metal working AMB in Stuttgart 2018. Due to the five functional areas of the digitalisation ( [1] , figure 2) the roadmap for the tool manufacturing industry is broken down accordingly. Figure 3 displays for each area the state of the art and the vision for the next years. Data as an enabler for the digital transformation Data acquisition and data processing build up the foundation of digital technologies and the digital transformation. Today in medium sized businesses, a big amount of data is being already collected and organized in ERP- Assistance systems to increase efficiency and compensate the shortage of specialised staff Assistance systems include all technologies, which relieve the worker from the exe cution of his tasks. The assistance systems currently available on the market essentially support users with selective information. Most of these solutions are purely expert systems that are neither mobile nor tailored to the knowledge and skills of the individual worker. In the future, these systems should be made simpler, cheaper, more user-friendly and adapted to the requirements of the work tasks [1/8] . When using digital assisfigure 1: Overview of the industrial revolutions and the technological enablers [16] systems, mainly for the order processing. Data concerning the whole product life cycle is rarely collected and used [1/2] . To enable an increasing digitalisation, data acquisition should be systematically expanded down to product level. This is made possible by using sensors on the machine and tool level, by accumulating, processing and providing data in real-time concerning machine, process and product. Due to the acquisition and evaluation of data, conclusions can be drawn concerning quality, tool life and from this a dynamic tool change can be initiated even before defective parts are produced [3/4] . In spite of some implementations of sensors on cutting tools, there is still a need for intelligent tools, which can combine data acquisition near the cutting zone by miniaturized sensors with data evaluation to return the results for control and adaption of the process parameters [1/5] . The growing use of sensors in cutting tools and machine tools reveals that in medium sized companies a high level of implementation has already been achieved in the area of data acquisition at the process level leading to an enormous amount of data and data types to be dealt with. However, this requires both IT infrastructures and Big Data algorithms, which can process large amounts of data in real time [6] . For medium sized companies, scepticism about Big Data applications is caused by risks related to ensuring data quality and security, protecting personal data and intellectual property rights [1/7] . Eventually, many medium sized companies are unable to see how data-driven business models can create revenue from their customers. 46 no. 2, August 2019
processes tance systems the workers get optical, acoustic or haptic signals through systems such as data glasses, headsets, RFID-gloves or sensor bracelets. These interactive assistance systems (IAS) provide important information concerning conditions (e.g. tool life, wear behaviour) and processes (e.g. quality) in real time and enable workers to make fast and data based decisions to create an efficient work flow despite a higher complexity of production processes [9] . Decentral production planning and digital business models as added value in the digital transformation The highest value creation, credited to the digital transformation is based on the structural change from centralised enterprise structures to a decentral organisation [13] . The vision of the transformation process entails the goal of a service oriented structure, in which every department, unit, machine and tool together form a system of autonomous units (Everything as a Service), which offer their service to the company and the production network [1] . For SMEs in the tooling market, service orienta tion today is mostly restricted to spare parts supply, logistic services and technical advice for tools and processes [1/14] . A substanfigure 2: Five functional areas of the digital transformation, according to [1] Today many engineering apps are developed, which allow real status and process data from production to be displayed at any time, anywhere and on any end device. In tool manufacturing, these applications enable SMEs particularly to access more IT with low investment costs, e.g. for the surveillance of capacities, of machines, process opti misation and control, the detection of critical operating conditions and quality management [10] . work pieces to be machined, but will become a central data source for the efficient control of all necessary production steps. This will demand a distinct identification of every tool e.g. by RFID or QR-code to allocate tool specific data in interaction with the network partners like machines and work pieces but also tool management systems or regrinding services [6] . In the field of machining, assistance systems are used, which - with the help of small apps - assist the worker in selecting appropriate tools and suitable cutting parameters or offer assis tance in gen erating auto mati cally the CNC code. These assistance systems offer above all to SMEs the possibility to embed less qualified workers in production processes. Digital technologies in interaction with production networks Most decisive for a sustainable economic success in the context of digital transformation is the integration of value creation processes within the single enterprise itself as well as the cross-company networking and integration of value creation networks. Unfortunately, due to a lack of data standards and communication structures, the degree of networking among SMEs is currently at a low to very low level [1/2/11/12 . The vision of the digital transformation in the processing industry involves an automated, cloud-based exchange of data (internet of things) between components, planning systems, cutting tools, manufacturing facilities and measuring instruments without human intervention. In the future, the cutting tools in the manufacturing process will not only be responsible for the quality of the figure 3: Technology roadmap within the five functional areas of the digital transformation, according to [17] no. 2, August 2019 47
