Engine Pattern Kaizen: Design and Implementation of an optimization algorithm to automatize production plans

Over the years, Toyota Motor Company has been able to adapt to the trends in demand and the changing climate of the economy by not burdening themselves with the increased carrying costs of storing finished goods or wasting precious resources on unnecessary production. Toyota Production System has allowed Toyota to react quickly to changes in the market and the economy remaining flexible and succeeding while others strive, even in hard times. This is attributable to its philosophy, which characterizes Toyota as one of the role-model not only in the manufacturing world, but also beyond its manufacturing walls to the entire supply chain. In an ideal world resources would be infinite leading to flexibility at all scales since companies would be able to change production plans and their capacity utilization when desired. Unfortunately, this is not the case considering that there are many factors that can vary companies’ expectations as efficiency, manpower, parts’ availability, and many others. Henceforth, companies need to analyse and produce according to their needs, setting beforehand, machines and equipment, skilled personnel, and cycle time of production. The scope of my thesis was to tackle one of the most difficult tasks in production planning, creating a production plan. The engine pattern calculation is a very important job that planners must do each month. It is about calculating the exact number of powertrains that will be produced in the plants the following month. And desegregate them into weekly, and daily production plans. The objective was to analyse the current situation by observing planners while they did this calculation, and afterwards, use an optimization algorithm through a computer program to avoid the manual calculation of this task, which is a non-value added one. This would not only, lead to the optimal solution, but also, free more time for critical thinking and analysis of production plans. The study starts with a brief analysis of Toyota production system and the importance of this project for the company. The aim of the optimization algorithm is to get a function that maximizes the production plan and minimizes the variation in the capacity utilization, using the optimum number of resources. Leading to Heijunka production plans. Heijunka production plans will enable production to efficiently meet customer demands while avoiding batching and results in minimum inventories, capital costs, manpower, and production lead time through the whole value stream. At the same time, I do an analysis at the different software that Toyota could choose to do this optimization problem. Eventually, I underline the assumptions and benefits to the company given by the final decision chosen. Finally, I compare real results obtained by the optimization algorithm and the one did by an experienced member. This conclusion will show the benefits of using this algorithm and the importance to allow more time for creative thinking. This in Toyota is known as “Jidoka”, which in Japanese, means automatization with a human touch.