A risk based engineering maintenance and spare parts planning model for a generic pharmaceutical company in the Eastern Cape

The Pharmaceutical Industry is facing substantial challenges due to the continuous evolving world of technologies, global competitiveness, price regulation, environmental and safety requirements. In this environment asset maintenance evolved and became increasingly important in business over the last couple of decades. Traditionally industry favoured a reactive maintenance strategy but over the years changed to proactive maintenance strategy due to the advancement of technology and skills of maintenance personnel. With increasing automation and mechanisation, production processes are becoming highly complex and the cost associated with asset maintenance has increased consistently over the decades. Studies have shown that about 15-70% of production costs can be attributed to asset maintenance and one-third of maintenance costs are wasted due to inefficiencies in planning. Furthermore, the selection of an effective maintenance strategy is a challenge due to maintenance output that is difficult to measure and quantify. This treatise will investigate the application of a risk based strategy on asset maintenance planning and spare part management of a pharmaceutical company and compare it to best practices. The theory of risk analysis was reviewed and risk analysis pertaining to maintenance planning and spare part management in the Pharmaceutical industry explored. Questionnaires were sent to selected engineering and relevant departments in order to analyse the challenges and good practices in the company relating to spare part management and maintenance planning. A risk based model for the pharmaceutical company was developed after the information gathered in the research. The recommendations were made in a practical approach by presenting the solution in the form of a flow chart. This model will enable the Maintenance Managers, Inventory Managers and Maintenance Planners to identify critical equipment, optimise maintenance schedules and plan spare parts purchasing more accurately