Simulating production risk at Volvo Powertrain - Developing a simulation tool for decision making

Abstract: How can a small fire at a subcontractor in the USA lead to a multimillion dollar loss at a Swedish telephone company, and how can a single machine breakdown lead to a complete production stop at a production company? With today logistics and production trends, where terms such as Lean Production, Six Sigma, 5S, and World Class Manufacturing are used every day, production companies are introducing streamline production facilities and supply chain where goods and raw material are delivered just in time, where buffer zones are reduced, and where suppliers are reduced to a single source. These are trends that strengthen companies’ competitiveness, but it also makes companies more vulnerable to risk events. Volvo Powertrain in Köping is implementing World Class Manufacturing in Köping, and they are aware that there are risks that can harm the production and delay deliveries to their customers. They were looking for a tool that could visualize the consequences of such event to enable quick decision making. From known historical events and from Volvo Powertrains request, a two folded purpose was developed. The first purpose was to perform a risk assessment on the production facilities at Volvo Powertrain in Köping and to find and analyze risks within the factory that has a high impact on the production. The second purpose of this master thesis was to develop a simulation model for a production industry that visualizing the consequences of a disruption and enables quick decision making. To make this possible, a single case study together with the empirical quantitative-based simulation methods was used whilst the theoretical foundation was based on the AS/NZS 4360: 2004 standard. A simulation model was developed using the probability safety assessment program RiskSpectrum. This required an accurate collection of information to reflect reality as good as possible. The information collected contained historical risk events, different machine flows, different article numbers, fire cells etcetera, resulting in a simulation model containing almost 400 machines, 200 machine cells, 170 article numbers, and 600 different flows. The result were transferred to a Excel-file making it possible for the user to search on a machine or article number, and to see what machine are connected to which article numbers, and which machine that are critical and cannot be replaced by a different flow in the production line. The simulation also showed that many articles produced are critical connected to at least one or more machines that cannot be replaced today by another machine or by a 3rd party. This master thesis does not intend to speak against new logistic and production trends, but rather to show how important it is to develop a strategy on how to handle risks when a risk event occurs. By having a well-developed action plan, a costly risk event can turn into a business opportunity.