Abstract
Process planning in manufacturing today focuses on optimizing the conflicting targets of cost, quality, and time. Due to increasing social awareness and subsequent governmental regulation, environmental impact becomes a fourth major aspect. Eventually, sustainability in manufacturing ensures future competitiveness. In this paper, a framework for the planning of sustainable manufacturing is proposed. It is based on the abstraction and generalization of manufacturing resources and part descriptions, which are matched and ranked using a multi-criteria decision analysis method. Manufacturing resources provide values for cost, quality, time and environmental impacts, which multiply with their usage within a manufacturing task for a specific part. The framework is validated with a detailed modeling of a laser machine as a resource revealing benefits and optimization potential of the underlying data model. Finally, the framework is applied to a use case of a flange part with two different manufacturing strategies, i.e., laser metal-wire deposition and conventional milling. The most influential parameters regarding the environmental impacts are the raw material input, the manufacturing energy consumption and the machine production itself. In general, the framework enabled the identification of non-predetermined manufacturing possibilities and the comprehensive comparison of production resources.
Highlights
The trend of personalization, growing global competition, and volatile market demands require increasingly flexible and adaptable production systems [1]
Laser metal-wire deposition (LMWD) performed on a universal laser machine at the IFSW was chosen as an exemplary manufacturing process
With the sustainable manufacturing framework, the paper proposes an ontology for production resources and part descriptions to realize process planning under consideration of ecologically aspects
Summary
The trend of personalization, growing global competition, and volatile market demands require increasingly flexible and adaptable production systems [1]. Service providers must balance production costs, time to delivery and product quality. This is an immense challenge, since the three parameters often show contrary effects. Today’s most promising approach is to handle this complexity by the digitalization of production systems and subsequent optimization [2], e.g., by virtual commissioning during the planning phase, automated sourcing activities during operation or numerical simulation to predict production on the process level. Sustainability in manufacturing must be included in the decision-making during process planning
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