Yuniawan, Dani ORCID: https://orcid.org/0000-0001-9343-0349 (2014) Simulation Modeling and Analysis for Productivity Improvement in the Production Line. Doctoral thesis, The University of Tokushima.

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Abstract

Lean manufacturing addresses the growing need for all types of organizations that drive process change and performance improvements in their organization environment and supports the evolution toward demand-driven supply networks. Lean principles are derived from the Japanese manufacturing industry. It is the set of "tools" that give contribution in the identification and steady elimination of waste (muda). As waste is eliminated, quality improves
while production time and cost are reduced. The key to lean manufacturing is to compress time by eliminating waste and this continually improving the process. Ohno (1988) defines waste as all elements of production that only increase cost without adding value that customer is willing to produce.
The total productive maintenance (TPM) is mostly regarded as an integral part of Lean. TPM originated in Japan in 1971 as a method for improved machine availability through better utilization of maintenance and production resources. TPM uses an overall equipment effectiveness (OEE) index
to indicate equipment and plant effectiveness. The technique works to eliminate the six big losses indicated by Nakajima, as down time (caused by equipment failure, set-up and adjustment), speed losses (owed by idling, minor stoppage and reduced speed) and defects (caused by process defects and reduced yield). The Japan Institute of Plant Maintenance promoted TPM which includes the
OEE in 1971. In 1988, Nakajima introduced the TPM to the U.S. OEE has since gained a lot of attention as the ultimate performance measure of a piece of equipment. Sohal et al., (2010), from survey results, found that OEE typically
advances from a base measure for efficiency (as its initial purpose), to being a tool to improve effectiveness for analyzing data to support continuous improvement objectives. It’s through the identification and elimination of six big losses, namely (i) breakdowns, (ii) setups and changeovers, (iii) running at reduced speeds, (iv) minor stops and idling, (v) quality defects, scraps, yields, reworks, and (vi) start-up losses. The first two affect Availability rate (A), the
second two affect Performance efficiency (P), and the last two affect Quality rate (Q). These three OEE elements, since being introduced by Nakajima until this research was conducted, already experienced several improvements involving a weight calculation method for OEE elements.
This study proposes a procedure to obtain weight settings of each OEE element and OEE estimation for productivity improvement in the production line. The first research proposal is sought to offer a procedure to cover the drawbacks of weighting OEE elements. The research motivation was initiated by several researches of OEE improvement, which met difficulty when determining the proper weight for each OEE element. The calculation results of OWEE and PEE by STP also showed better results than the original OEE for the simulation model case study. From the result analysis, it can be concluded that the outcome of this research experiment can be implemented in OEE with a weighted method, among others; for example, in PEE (Production Equipment Effectiveness) as well as OWEE (Overall Weight Equipment Effectiveness). A simulation model was chosen because it is able to mimic a real production line and therefore act as a suitable experiment tool. This study provide a lean overview followed by a description of how simulation is being used to enhance lean performance. This study offering simulation as the lean way to implement and accelerate the TPM. The STP (Simulation Taguchi method Procedure) provided characteristic mapping of OEE elements through a response table. Naturally, even though STP seems to be difficult to implement, the outcome is worthwhile. Moreover, the company will have obvious data to consider when making decisions for the improvement of priorities in their production line. The second research proposal offers OEE enhancement scheme, which provides a company with the appropriate information for decision-making on priority improvement in the production line. By using the Taguchi method and simulation as an experimental tool, this scheme can measure and estimate the contribution for each OEE element to an OEE score. This procedure can be
implemented in a specific WS or in a production line if the factory is made up of more than one manufacturing line. They provide measurements for each OEE element in order to observe the extent of the influence the simulation
experiment has on the OEE elements and scores. All of those research proposals are to improve the OEE as a KPI in the
factory. In order to meet the objective of the TPM itself, increasing the sustainability of the company by continuous improvements.

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