Exploring The Efficiency – Flexibility Dilemma Of A Manual Assembly Process

Abstract: The purpose of this study was to find a method for exploring the potential of increasing the efficiency of a manual manufacturing process while simultaneously maintaining the flexibility and the ability to adjust to changes in demand. The study has been conducted in cooperation with Scania CV AB Engine Assembly in Södertälje, Sweden. This explorative study has been conducted using a framework mixing traditional Quality and Process Management literature, with theories of Innovation Management and ways of designing a production process. The framework was designed by focusing on perspectives to help explain and optimize the dynamics of a manual assembly process characterized by high variation. Increasing the efficiency has included the elimination of waste and disturbances while creating opportunities for continuous improvement. Improving the ability to adjust to changes in demand and volume has included reorganization of the information flow. Activities aimed at increasing the efficiency and improving flexibility requires a base of information which is sufficient and enables fact-based decision-making. An analysis of the current state was conducted using triangulation of data collection methods. Interviews, observations, focus groups, surveys, and numeric data was analyzed. Tools of Quality Management, Lean Management, and the Productivity Potential Assessment method were used to develop a framework for evaluating a manual production process and aim to collect, process, compile, weigh, prioritize, and visualize the processes and the identified challenges. Identification of improvement activities and the design of a future state was conducted through extensive interviews and focus groups and by interpreting relevant literature. Mapping of the current state generated five primary challenges which are complicating the daily work in different ways. The challenge estimated to have the highest overall impact on the studied process is Time Data Management. This challenge refers to the lack of valid and correct data on which to accurately plan and control the process.