The concept of “make-to-order” (MTO) type companies is to produce the products just-in-time and improve the customer satisfaction. These types of company produce a high variety with low volume requiring a frequent setup operation. The shorter setup time will reduce the manufacturing lead time and hence increase the productivity. Unfortunately, most of the MTO type companies suffer with high setup time. Thus, single minute exchange die (SMED) concept is developed which consist of four stages: internal and external setup are not distinguished, separating internal and external setup, converting internal into external setup and streamlining all aspects of the setup operations. The main objective of using SMED concept is to accomplish setup time in less than 10 min. In this case study, the SMED concept being applied to convert internal setup to external setup which involves the activities of ink preparation and test printing. In the stage three of SMED concept, feasible solutions has been applied to fulfilled the objective. The result of implementing SMED concept in MTO type companies is the improvement in the productivity and reduction in the setup time. The improvement of productivity for this case study was 29.15%.

Random in-process quality control (IPQC) is conducted in one of the departments in a circuit board manufacturing company, Company A, which produces high-mixed products, and results in complete failure of ensuring the quality of parts produced. Consequently, defects occur on the parts produced, leading to high rejection rate. This high rejection rate eventually results in high cost of non-value-added activities, which include rework of rejected parts. This paper introduces quality planning to ensure the quality of work-in-progress (WIP) parts in the production with discrete event simulation (DES) software. A series of experiments is conducted by using varying parameters, including flow patterns of parts in the shop floor and number of IPQC inspector, to assess the significance of these parameters on the performance measures relevant to quality perspective. Statistical analysis is conducted on the simulation results via ANOVA. Findings from this research prove that varying the parameters has a significant effect on the performance measures.