Many companies are experiencing an increasing demand for small series or even unique products. This is causing a large increase in complexity within the production apparatus. Manual assembly remains important here because of its flexibility. However, assembly tasks are becoming increasingly complex and many companies are trying to provide operators with additional support.
Industry 4.0 (cyber-physical systems with a.o., communication and monitoring) is a way to deal with this but the product itself should not be forgotten. After all, operators often use instructions insufficiently because they rely on their own insight and experience, and start interpreting the product to be assembled in the assembly context themselves. This can lead to errors in a context of small series and larger product families (lower efficiency, increase in costs to correct this). Instructions can also undermine the sense of competence and autonomy (two factors strongly linked to work motivation). This can lead to demotivation in these operators, burnout and absenteeism.
Therefore, solutions are needed that take into account the operator in assembly. In order to address these problems and maximize the response to the needs of the operator, a methodology has been developed that starts from product development and takes into account the needs of the operator during manual assembly: Design for Assembly Meaning (DFAM). This is especially important because the operator mainly intuitively determines the assembly or disassembly steps based on the interaction with the product to be assembled or disassembled. The methodology was developed during a PhD at UGent (Parmentier et al., 2019; 2020; 2021) and aims to design products that can be assembled much more intuitively with fewer assembly errors, less need for instructions and responding to the need for competence and autonomy. This has many advantages for the assembly process, the efficiency of the operator and his work motivation. The methodology not only responds to the needs within a normal assembly context but also builds the bridge to an industry 4.0 assembly context where operators can be supported through Augmented Reality (AR) and where monitoring of the assembly process is possible. Moreover, developments in digital production techniques such as additive manufacturing (AM) have made it possible in certain contexts to make adjustments to both components but also certainly to jigs and fixtures in relation to these components. Moreover, the methodology can also be applied to the manual disassembly process which in combination with the manual assembly process can facilitate the maintenance, repair and upgrade of the product, this in relation to the full product life cycle.
Within the Tetra project we want to implement this methodology in various business contexts and on various products. We want to get to know the company-specific factors in order to optimize the methodology in function of these factors as well as to quantify the impact of the methodology in various company contexts. We also want to develop demonstrator case(s) and training tool(s) in the project that will enable designers in companies to implement the methodology in a simple and tailored way.