Development of a decision support model to capture and reuse the tacit knowledge in injection mould design for small and medium-scale enterprises

Abstract

Injection moulding is one of the most economical ways of manufacturing parts in large quantities. Here, achieving the expected quality of the finished products largely depends on the design and manufacture of the moulds. The design process of injection moulds is well established, but it is resource-intensive, requiring investment. Inability to invest in latest software tools and to employ experts are major concerns for small and medium-scale-enterprise (SME) mould manufacturers. Thus, they continue to rely on personal practical experience rather than modern and contemporary technology leading to a technological gap between the large- and small-scale mould manufacturing sectors. While explicit knowledge can easily be transferred from one generation to the other, there is no proven system in place to capture the tacit knowledge of employees, store it, and reuse it appropriately. Transferring the tacit knowledge to the successors has been difficult as understanding of the technology live within the individuals. Therefore, this research aims to identify the critical issues faced by the SME injection mould manufacturing sector and develop a decision-support model to capture and reuse the tacit knowledge within the organisations. Initially current design practices, procedures, and problematic issues were identified through several rounds of surveys and interviews with experts (n=15) from the local industry. The study revealed that the local SME sector Injection Mould Design (IMD) industry is diminishing despite the increasing global demand. This study further identified several problematic areas, where retaining the knowledge of the experienced personnel at retirement is the major burning issue. Several knowledge management (KM) models are in practice, yet they cannot be readily implemented as a solution to overcome the issues specific to the SME IMD industry. Therefore, a framework for capturing and reusing tacit knowledge was developed. In order to enable implementation of the framework, a decision-support model was also developed to support the decision-making process of IMD. Finally, the developed model was validated through case studies (n=4) in different industry settings. The decision support model to capture tacit knowledge can be used to design injection moulds with relatively simple components, mainly designed and manufactured by the SME sector mould makers. As future work, the functionality of the model can be improved by integrating artificial intelligence (AI) tools to introduce self-learning capability.