Background: - Founded in 1924, Lee Industries has evolved from a tin can and heavy duty kitchen equipment manufacturer in to a global leader in process systems and fluid transfer equipment - Kettles, Tanks, and Horizontal blenders are the three main product types that Lee Industries currently produces. - Lee Industries is a leader in the design and manufacturing of stainless steel equipment for the food, pharmaceutical, cosmetic, and chemical industries. - Lee has operated without any industrial engineering presence for over 25 years and is using this project as a gateway into using industrial engineering expertise to improve their facility. Problem Statement: - Due to increasing demand of Lee’s products there is a need for a model to help identify bottlenecks, analyze effects of different demand scenarios on shop floor operations, and identifying needed process improvements. - In light of the time constraints of the project the team focused on the most popular product, kettles, to model and serve as a baseline model to expand upon and make product specific observations. - The project’s overall goal was to develop a discrete event simulation model that accurately depicted the production of kettles on Lee Industries shop floor. Approach: - Identified processes and operations for developing a kettle. - Collected and manipulated data, such as processing times and resource capabilities, to fit the model. Used a Log-normal distribution to account for variability of operations. - Developed, verified and validated model. Assumptions: - Mass customization is difficult to model in SIMIO, so the group created a model that assumed all standard parts were present. - Standard times provided by Lee Industries were used as processing times in the SIMIO model. Future Work: - Lee has a variety of product lines which are not included in the current model (tanks, horizontal mixers, fluid transfer equipment, etc.) - Most products do not contain all possible parts; therefore, a variability of whether or not certain parts are included should be designed. - Develop demand scenarios to analyze how different product mixes would effect shop operations. - Include engineering design time based on customer model. - Evaluate whether another statistical distribution delivers better results. Analysis: - After running the model, several bottlenecks were identified, such as: welding, grinding and assembly stations. Recommendations: - By adding additional resources or exploring different methods to accomplish certain processes Lee Industries could see an increase in overall throughput. - Developing a linear flow to minimize waste movement of parts and materials. - Standardizing kettle models to reduce variability as well as engineering design time. Benefits of Simulation Modeling: Evaluate impact of long term events in a short period of time Evaluate changes/projects without executing capital investments Test “what-if” scenarios and analyze possible impacts Lee Industries – Discrete Event Simulation Model Maureen Mittura, Alexandra DiNatale, Kyle Sardinia & Samuel Kresky