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Development of a software as a service to optimize the placement of ceramic pieces into heat treatment furnaces


The production of ceramic pieces is a process composed by several phases. Initially, a mix of compounds and the molding of each piece is performed. Thus, a machining phase removes the imperfections left by the mold in the pieces. After this phase, the firing (heat treatment) is performed, in which the piece goes through a period in high temperatures to acquire the necessary strength and quality. To finish the piece a rectification is performed. Between these phases, the firing phase has great relevance. In this stage, the pieces are placed in furnaces where they stay up to 50 hours at temperatures up to 1640 degrees Celsius. These furnaces are heated using electricity or LPG (Liquefied Petroleum Gas), resulting in high consumption of resources. Furthermore, the environment in which these furnaces are arranged is hot, creating discomfort for the employees. Selecting the pieces that will be in each furnace and defining the arrangement of these pieces in each level of the furnace is fundamental for reducing the number of furnaces needed and the total firing time. In addition to speeding the furnace assembly, the firing planning reduces the chances of an unbalanced load. If an unbalance of the load occurs during the firing resulting in the moving the pieces, they can be affected and consequently will be discarded. Furthermore, the planning has a direct impact on the orders control and their delivery dates, reducing or eliminating delays in deliveries if performed properly. To the best of our knowledge, this problem has no reference in the literature. Solving this problem autonomously and optimally is aligned with the objectives of the Industry 4.0.In this scenario, the goals of this project are to develop a Software as a Service (SaaS) aiming to reduce the number of furnaces needed for firing the ceramic pieces and meet the demand of the pieces on time. Because it is a cloud computing service, companies will not need to invest in computers with high performance or with specific settings to solve the problem. The software will be intuitive, not requiring high technical knowledge to be used and will be efficient on the time of response to the problem, speeding up the process in the company. The solutions will be of easy interpretation, accelerating the pieces selection and their packing in the furnaces by the employee. To achieve the objectives, combinatorial optimization techniques will be used along with web programming languages. The expected result is a SaaS application that assists the company to perform the firing planning, with solutions of good quality that reduce the resources consumption and the completion time of the order, increasing industry productivity and profitability. Also, the solution will be easy to interpret, reducing the time the employee spends allocating the pieces in the furnace, a task that is performed in a place of high temperatures. The technical feasibility of developing this product was proven during the PIPE FASE 1 project (2017/08218-6) and, in the PIPE Training in High Technology Entrepreneurship, promoted by FAPESP, it was possible to prove the interest of a large number of industries in the product. (AU)

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