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Power Semiconductor and Electronics Manufacturing 4.0

Periodic Reporting for period 3 - SemI40 (Power Semiconductor and Electronics Manufacturing 4.0)

Reporting period: 2018-05-01 to 2019-04-30

Electronic components and systems are key drivers for the innovation capability of European industries, generating economic growth and supporting meaningful jobs for citizens. The ambition of SemI40 project is to implement technical solutions into the pilot lines of the industry partners. They are complemented by 30 challenging industrial use cases, representing real supply chains being also assessed regarding their technical, social and economic impact as well as future working conditions and skills needed. Applying “Industry 4.0”, “CPS”, “Big Data” and “Industrial Internet” technologies in the electronics field requires holistic, complex and cooperative approaches. The selected main objectives of SemI40 are: i) to balance system security and production flexibility, by providing reference demonstrator solutions for increased safety and robustness against cyber-attacks in vintage production environment; ii) to increase information transparency between fields and enterprise resource planning (ERP), by enhancing big data in semiconductor industry through enrichment of large-scale databases with semantic technologies; iii) to manage critical knowledge for improved decision making and maintenance; Iv) to improve fab digitalization and virtualization; v) to enable automation systems for flexible distributed production, by enabling optimized production and implementing full single wafer traceability.
"Objective 1 “Balancing of system security and production flexibility”: the work on the dependability model for CPPS allowed identifying first dependencies between technical/social factors like security solutions and second implications on availability and required training / new processes. For the integration of legacy equipment is available a solution that ranges from secure gateway to translators between legacy protocols and Industry4.0 protocols. The iteration of the security framework and services was implemented for the communication between external partners in the supply chain. Host-based and network-based anomaly detection solutions were trained on industrial network data in addition, based on the dependability model, a self-adaption framework was developed.
Objective 2 “Increased information transparency between fields and enterprise resource planning”: a state of the art Supply Chain Management software to control internal and external production facilities were implemented. The development and integration of the fundamentals for the visualization, which is built on a lot genealogy in one system, could be finalized. A demonstrator is running at a tests system and a first release is running at a productive system. For statistical evaluation of customer order behaviour a final implementation for SPC in Supply Chain method was realized based on SAP Business Objects and R-Studio. The last activity aiming at improving the transparency and traceability of components along the production process presented some challenges due to the fact that the MES-implementation was more difficult as expected, but finally was implemented.
Objective 3: “Management of critical knowledge decision making and for maintenance"": the goal of the associated activities was to establish algorithmic approaches tailored towards the use cases, while creating synergies between the use cases via sharing of best practices and making use of consolidated algorithms. A number of sophisticated machine learning and data science methods have been employed and even allowed to go beyond the current state-of-the-art in selected fields. Demonstrators for different industries’ use cases, were refined and developed, some of them are already used in different production environments.
Objective 5 “Automation systems for flexible distributed production”: the MES rollout in semiconductor power module production line has been continued and the new MES rollout at power module production was realized. The development, preparation and organization completed and a completion of the production pipe cleaner phase and the full rollout at the first and second plant at a different location realized. A very successful cooperation between two Portuguese partners a system provider and end user did start. The setup of a demo environment could be finalized. Together they developed a solution to toughen up MES with enhanced functionalities. A functionality was implemented to simulate the upcoming Fab behaviour including a corresponding dispatch list as an output of the Fab simulation this allows an optimized lot dispatching based on simulation results.
Within the third reporting period the task ‘Implementation Support for industrial pilots’ was successfully completed, A comprehensive review of the state-of-the art on impact assessment approaches and models used to create a tailor-made, three-step, multi-method impact assessment was applied. The industry partners provided a self-assessment of the implemented solution approaches, as well as a series of impact factors, which had to be quantitatively rated. Four defined focus use cases received special attention by the evaluation experts and the quality of these assessments was further enhanced. For one of these four focus use cases was conducted a deeper and innovative quantitative impact analysis that could be used as impact assessment of use cases in other industries. Facilitating knowledge transfer within SemI40 is one of the three main objectives. 40 knowledge transfer activities have been identified between the more than ~750+ employees working in four domains, secure cyber-physical production systems, agile manufacturing, machine learning and decision making and virtualization/digitalization, to finally identify valuable synergies without violating the IPs of the industrial partners.
The consortium had a strong will and ambition to disseminate, distribute, transfer and exploit the knowledge, experience and relevant project results to the European as well as to the global community.
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The project provides results beyond the state of the art in many I4.0 industr fields, e.g. safety and robustness against cyber-attacks, in supply chain control integration -visualization, in web based smart maintenance and sensors, wafer boxes tracking, advanced wafers transportation and swarm autonomous mobile robots, smart sensors integration, planning and processes execution, ... only to cite some of them. Some technical expected impacts (this list is not exhaustive) are: i) reduce the troubleshooting time and increase the availability of the production facility. ii) Mitigate potential attacks. iii) Error rate and failure rate can be reduced, quality increased. iv) Support department/s in utilizing its/their production work centers more effectively, increasing the productivity and leading to a reduction of production costs. v) Better response to customer requirements, ensures a more accurate forecasting and increases the customer satisfaction. vi) Maintain and possibly improve the market position. vii) More stable process and processing time. viii) Exhausting and monotonous control activities of employees, previously responsible for manual inspection, are changing to a more varied and thus more satisfying activity. ix) Reduce energy manufacturing systems production costs. x) Autonomous robotic transportation systems can optimize the overall utilization of the production line.