Approaches for automated and computer-aided work plan generation for adaptive manufacturing process chains in one-off manufacturing - a literature review

Abstract

Current trends such as mass individualization, matrix production, cloud manufacturing and production as a service can be addressed by implementing adaptive manufacturing process chains. Adaptive manufacturing process chains contain alternative manufacturing options at several levels (e.g. feature-based geometry sequence, manufacturing methods, production machines, clamping systems, fixture positions, tools or processing strategies) to be able to continuously adapt to the real time conditions of a manufacturing environment in the best possible way under given target variables. Currently, the design of process chains is often manual and based on implicit empirical knowledge, which on the one-side leads to non-optimal process chains and on the other side does not include alternative manufacturing possibilities. The required effort for implementing adaptive process chains is thus opposed to high costs and complexity in work planning. In this paper, a literature review is conducted to identify and evaluate approaches in the scientific literature for the generation of work plans of adaptive process chains in one-off manufacturing. The literature review is divided into three phases and is broken down into six steps. The preparation phase defines the scope of the research. In the implementation phase, approaches are first identified utilizing a keyword analysis based on the theoretical and practical principles of work planning and selected in a 2-step selection process. The evaluation of the relevant approaches by using defined evaluation criteria enables the identification of research deficits for the derivation of further research questions. The literature review in this paper concludes that no approach addresses all the different aspects of work planning comprehensively. In particular, the interactions of individual decisions between the planning dimensions are insufficiently considered.