Mapping of manufacturing data flow: A project in collaboration with Toyota Kirloskar Auto Parts

Abstract

Toyota Kirloskar Auto Parts (TKAP) is currently facing challenges regarding their data management processes. Being a traditional manufacturing unit, TKAP’s information flow happens manually over multiple paper documents such as product specification documents, inspection request forms, maintenance schedules forms, audit sheets, engineering drawings, kanban cards, etc. This manual way of information handling is bound to be error-prone and time-consuming and effectively increasing the manufacturing costs. The Toyota units have to overcome this inefficient data management process to be the pioneers of efficient and cost-effective manufacturing processes. There has been a push from the upper management to move towards Industry 4.0 and Digitalization. But, the investment of required IT systems would be very high and the integration of data flow in each and every process in the organization is not simple. This process of revamping the existing data management practices was taken up by the Quality Control Team of TKAP. Our objective was to provide the management team with solid frameworks of tackling the issue and provide a detailed study on the Business Process Management Techniques such as Flow analysis, Non-value-added analysis, Business Process Re-engineering (BPR), String diagrams, Value Stream Mapping (VSM), Clustering, etc. Once the frameworks have been put forth, we would analyse a particular process in the organization namely “Inspection Management” and apply the concepts learnt to build a robust data management process around it. The suggested practices should also be scalable throughout the organization.