Cost-conscious manufacturing – Models and methods for analyzing present and future performance from a cost perspective

Manufacturing is an industry in which the effects of globalization are obvious. Manufacturing costs are a key factor in this respect and affect, for example, decisions about offshoring, i.e., moving production abroad. If Sweden and other Western countries are to maintain large manufacturing sectors, they must be competitive, making cost one of the most critical parameters. The work presented here seeks to develop tools for cost-conscious manufacturing. These tools should provide insight into how well a manufacturing system is performing and support the analysis and prioritization of manufacturing development activities. To achieve this objective, two research questions were formulated. The first research question (RQ1) concerns how a general cost model should be designed to take into consideration the most important process-near parameters influencing manufacturing system performance. A cost model developed in accordance with this research question includes critical parameters affecting performance, such as cycle time, setup time, and performance loss parameters. The model is centered on the processing steps involved in processing a part. The losses occurring in the processing steps are important in the model, so the links between structured, detailed monitoring of the loss causes and their impacts on costs are emphasized. Modified versions of the model to analyze volume flexibility and downtime variability are also presented. The second research question (RQ2) concerns how such a cost model can be used in practice, i.e., the requirements and conditions for industrial use. Implementation in an automotive company indicated that the model was applicable in this context and that interesting insights into manufacturing costs could be gained from using the model. A study of the industrial conditions for applying the cost model identified software products for collecting manufacturing loss data that support the level of detail needed for model input, but found that manufacturing companies do not necessarily collect such detailed data. A demonstration program developed based on the databases available in a collaborating company indicated how the cost model could be used practically in a company. The somewhat deficient detail in the collected loss data, found in the above study, led to an inquiry in another company into the pros and cons of collecting highly detailed performance loss data. The results identified more advantages than disadvantages with collecting more detailed data: the operators responsible for data collection did not perceive any particular difficulties with the increased detail and the production manager believed that the increased detail led to better knowledge of performance losses