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EN
his work, developed as a case study, propose, describe, and evaluates an implementation of a pull system in a SME company producing polymeric components for the automotive industry. The production system of the company was based on the push paradigm, which creates high stock levels and high lead times. The main purpose was to develop a pull production system controlled by Kanbans in the painting line. To achieve this goal, this case study demonstrates the application of relevant lean tools, such as, VSM, SMED, Kanban System, Supermarkets and Leveling. Through the SMED’s application, it was possible to reduce the setup times in 38% and make annual earnings of approximately 83000€. The application of a Kanban System, Leveling and Supermarket enabled the WIP’s reduction between injection and painting in 56% and, also, between painting and expedition in 45%. Also, the lead time decreased and the value-added time increased. Thus, this is an exemplary case study for the implementation of a pull system and can be used both by practitioners and researchers interested in this theme.
EN
The purpose of this research is to develop a Lean-RFID based waste identification system (LRWIS) for small-medium manufacturing companies. The specific objective of this research is to develop and implement the LRWIS from integrating the appropriate lean tools and advanced technologies for wastes reduction and inventory management. Subsequently, the framework was converted into a system for a small-medium sized wood processing manufacturer in Malaysia and integrated into a computerized program. The LRWIS can monitor real-time inventory and production status so the manufacturer can optimise the quantity of the primary products and deliver them on time as per the RFID information of each container. The manufacturer can also make decision instantly for controlling and changing different products in the production progress. The system provides simple constructed framework under a low cost infrastructure, yet it is of practical value in reducing the wastes and also optimising the production process.
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