iDev40

Short description - The iDev40 project encompasses the entire integrated value chain of development and manufacturing—from concept to product and from supplier to end customer—and covers a wide range of development teams across various fields as well as diverse manufacturing tasks across geographically distributed locations, including related support activities such as order management, training, and service and application support. As part of the project, the partner University of Applied Sciences Zwickau (WHZ) will explore innovative application scenarios for material flow simulation in semiconductor manufacturing at the network planning level. Building on preliminary academic work on backward simulation, specific requirements from the industry partners will be implemented and validated in a predictive tool. To this end, the methods to be used must be significantly expanded and further developed to ensure their practical applicability.

Project Duration:
Jun 1, 2018 bis Oct 31, 2021

Project Management:
Prof. Dr. Christoph Laroque

Partner:
EU, BMBF, SMWA

Efficient design of production processes plays an essential role in successful production planning within a company. In the future, conventional planning tools are to be optimized using backward simulation. A team led by Prof. Dr. Christoph Laroque at the Faculty of Economics at West Saxon University of Applied Sciences in Zwickau is now tackling this task as part of a research project. The sensitive and complex production processes involved in semiconductor manufacturing are expected to be the first to benefit from the results.

The entire electronics industry—and the European semiconductor industry in particular—employs well over one hundred thousand people. In Germany, this primarily affects the cities of Dresden, Munich, and Regensburg. In the long term, jobs in the latter can only be secured if technological developments and the corresponding manufacturing know-how align with the international market. This also applies to information systems for work preparation and production planning. The increasing demands of Industry 4.0 on manufacturing companies are prompting the semiconductor industry to adapt its development, logistics, and manufacturing processes to future value chains.

In recent years, corporate objectives have shifted and evolved from achieving economically optimal production capacity utilization to meeting delivery deadlines. The introduction of new products is particularly challenging due to significantly shorter product life cycles. Compounding this challenge for the semiconductor industry is the fact that the production process is extremely complex. In some cases, products must pass through many production steps and, in some instances, pass through specialized equipment multiple times. Furthermore, production at different locations can sometimes result in significant scrap. This scrap may need to be eliminated by producing specific quantities of components. The comprehensive production process pushes current scheduling tools to their limits.

Various practices are employed to fulfill the tasks of scheduling. Methods such as integer optimization, heuristics, and forward and backward planning have proven effective in the past for generating initial solutions, which are utilized in iDev40. The planning objective therefore determines whether a forward or backward approach is taken. In capacity planning, the planning phase is approached forward to minimize the time between start and completion. In contrast, when scheduling dates, planning is performed backward to ensure that guaranteed delivery dates are met. The greatest drawback of the product planning and control methods currently in use is the sometimes significant discrepancy between target and actual plans. This is due to the simplification of production systems to reduce planning and computation time. Heuristic methods are primarily used to solve complex models; these methods have reasonable runtime even for large-scale problems. To ensure the maintenance of concrete plans, discrete event simulation is employed. This approach addresses the problem-solving of highly complex models. The starting point for the simulation to be performed is a specific production sequence. The result provides insight into the feasibility of the workflow and the schedule. If these are found to be unfeasible, a potential production plan must be developed using systematic searches. DES models accurately reflect reality and account for real-world variability. Also worth noting is the diversity of modeling options: resource dependencies, maintenance, and workflow, priority, or setup rules.

Simulations and heuristics are primarily used to analyze and solve forward-looking process planning problems. In backward-looking process planning, however, these methods are not used, despite the advantages that simulations offer. Forward and backward simulations do not represent a pair of opposing values. The two functions cannot be used to rule one out in favor of the other; rather, they can reveal different states at the same simulation time. To ensure the reliability and accuracy of the process plans, backward simulation also incorporates elements of forward simulation. To date, no relevant experience has been reported regarding backward simulation in combination with detailed maintenance and repair planning. The team led by Prof. Dr. Christoph Laroque will address this issue in the current iDev40 research project.