Local manufacturing small and medium enterprises (SME) have faced continuous challenges in competing with manufacturing firms of scale on the global market. Factors such as the presence of a traditional organisational structure and inefficient utilisation of resources have contributed to the challenges faced by local SMEs in keeping up with regional and international competitors within the manufacturing sector. To investigate the aforementioned challenges, a case study was conducted on a local bottle manufacturing SME which sought to improve their system performance across their Plastic Injection Melding (PIM) operation. Using strategies in the form of lean manufacturing as well as ARENA® simulation software, the challenges identified within their operation were observed and mitigated using key performance indicators. Lean strategies such as Heijunka, Kanban and Six Sigma were utilised as possible methods of reducing waste within the existing simulation model. When comparing the key performance indicators from the simulation, findings highlighted improvements in the Work in Process (WIP) and Waiting Time (WT) by 84.78% and 98.03% for the entire operation. A cost-benefit analysis was carried out to identify the most financially feasible strategy in purchasing the resources that were required for the strategy’s integration into the actual system.

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A simulation case study was conducted to assess the utility of predictive maintenance and database management for lean maintenance applications within a Petroleum Company. At this company the maintenance of pumps was performed internally where feasible. The study explored a proposed lean strategy on the operations of three departments related to the maintenance of pumping equipment. These departments were, the Pump Shop, Stores Department and Shipping and Receiving. Rockwell Automation’s Arena® simulation software was used to study existing and proposed models of the maintenance system and track the key performance indicators of Flow Time, Waiting Time, and Work-in-Process. Analysis of the performance indicators showed a 76% and a 96% reduction in average Flow Time and Waiting Time, respectively. No difference was determined for Work-in-Process at the 95% confidence interval.

This paper looks at applying predictive maintenance and automated data storage and retrieval to reduce waste within a Petroleum Company. In this company, all pump maintenance was performed internally. The study explores the potential effect of the proposed strategy on the operations of three departments relevant to pump maintenance. These departments were, the Pump Shop, Stores Department and Shipping and Receiving. Rockwell Automation’s Arena® simulation software was used to model an existing and proposed maintenance system comprised of these three departments and track the performance measures of Flow Time, Waiting Time and Work-in-Process. Analysis of the performance measures revealed a significant reduction in average Flow Time and Waiting Time by 76% and 96% respectively with no significant change to Work-in-Process.

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