Proceedings of the 2013 Industrial and Systems Engineering Research ConferenceA. Krishnamurthy and W.K.V. Chan, eds. EVALUATION OF PRODUCTION ORDERS SPLIT IN ELECTROSTATIC PAINTING COMPANY Abstract ID: 125 Abstract This article aims to make a diagnosis to production scheduling system in a company dedicated to metal coating with electrostatic paint. One of the most common problems in the operation management is to determinate the optimal sequence to execute in a command set or in an order batch (order lots) seeking to minimize the times of use and set up of each machine. Considering the efficient allocation, this problem concerns to schedule a set of tasks that needs to be done for one or a group of machines arranged in correct sequence; this “Sequencing problem” considered a NP (complex) when the number of machines is greater than or equal to 3. Every single task follows the same route of manufacturing; where a machine cannot process more than one task at the same time. The assessment of production orders with subdivisions, provides the initial stage of the characterization and diagnosis of the production; under this conception those tasks that minimize the speed of the production flow were identified (Bottleneck). The research results show that there are problems in the processing and delivery of the finished material. Keywords Sequencing, subdivision, machine setups, Flow-Shop, Scheduling 1. Introduction The most important part of an organization is the system behind the product, production systems are classified according to the layout of machinery and departments within the organization. The types of production systems can be classified by Job Shop and Flow Shop. For these cases the variables are the number of different products manufactured by a company, the types of orders, sales volume and the frequency of repeat orders, and strongly influence which would be a more efficient production system for a specific company. Flow Shop System or continuous production are characterized as those in which all jobs are processed in the same order on all machines, this is the typical situation of continuous mass production but not unique to this type of production, the production process of a specific item can be interrupted, setup machine and restart the manufacture of another article of the same family. That’s known as batch production. The batch production, the production system is used by companies that produce a limited amount of a product each time, with increasing amounts beyond the few that are made to start the company; the work can be done in this way. That amount is called limited production lot. These methods require that the work relating to any product to be split into parts or operations, and each operation is completed for the entire lot before taking the next step. It is in batch production where the production control department can produce the greatest benefits, but is also in this type of production where the greatest difficulties to organize the effective operation of the production control department. During the manufacturing batch materials are always at rest while the batch finishes processing. Rest periods of any unit in a lot of 'n' units added (n-1) / nx 100 percent of the total production time per batch. This is characteristic of batch production, where the work content of the material increases irregularly and gives rise to a substantial amount of work in process. 2. Research Overview 2.1. Objective Characterize and evaluate programming problem and the sizing of production orders in a manufacturing system, which works in a Flow Shop, considering the time and cost of setup machines, termination costs early or late, and fractionating batches according to the determined sequence. 2. Process Characteristics The production process of electrostatic painting represents a Flow-Shop problem. Problem Description AMI and Industrial Metal Finishing born in 2007 with the goal of providing innovative applications in the process of electrostatic powder coating. o Input volume (amount) is high. Labor o Type of repetitive task. o The type of market is large (mass production). . the order of the machines will always be the same. you may not be achieved with the proposed delivery requirement. the number of pieces that can feed the line is limited and the only machine that needs changes associated with each production order is the camera of paint.3. Because production orders are received where most times the color pattern changes for each structure to paint and terms (time) of delivery are different. Problem formulation ¿How can you optimize the functionality of a production system using fractions of lots of purchase orders? 2. complying at all times quality parameters demanding customers. allowing customers to have new options to complete their manufacturing processes.4. 2. For the specific case of this process is important to consider that the rate of the production line is constant. or 3 Last Name Yet 2.No Author 1. each machine performs a single task and work at the same time work (pieces) go through each machine once. o Sequential inflow o Variation in the characteristics of the product is low. Currently has an excellent infrastructure to advance processes 700 m2 "Just in time".2. Figure 1: Diagram Production process electrostatic paint Consider the following workflow: • • Product: o Large batches to allow continuous production. ! [ *. however when a processing unit starts a machine must finish. [ *# + . Capital o Investment in machinery and raw materials is high.No Author 1. indicating how many and what size are the subdivisions of each order. o They keep inventory levels low (paintings) depend on customer requirements.j) E(i. The problem is to achieve minimize the processing time of all jobs.j=1.…. Methodology There are n orders where each Kn consists Product number n. … . the order fractionation means cannot generate product fractionation beyond the maximum permissible amount is equal to the product requested by the request.N.( … . … .j) = completion time after the delivery date of job (i. Verification o The production control.j) = denote the J^th job of product i i=1.j) = Objective Function = ∑" [ℎ! & '( [ *. [ * # − ! [ *.j) = delivery time j of product i h(i.j) = time of job process j of product i d(i. o The service is high as long as the production schedule.j) = completion time before the delivery date of job (i. or 3 Last Name Yet • • • o The skill required to perform the tasks is low. 5 (2) (3) (4) . orders can be executed partially.j) = completion time of job (i. [ *# + /-( [ *. [ *# + *# + + 1! [ *. [ * #* 3 = 1. o The equipment used is unique for a special purpose.j) = keeping cost the unit of job j of product i at the in inventory per unit time TCU(i. [ * # 3 = 1. o The planning depends on the amount of production orders entered. [-( [ *. [ * # ≤ -! [ *. which must be processed on m machines whose processing times per unit of output are Tij. [ ( [ *. [ * # − -! [ *. 5 7!0.! [ 0 *. [ * # + /! [ *.j) T(i. Objectives o The cost of maintenance and supply is low.j) = penalty for finishing after the delivery date units job j per unit time SC(imp) = prepare cost of moving the produce i to product g ST(imp) = prepare time to moving the produce i to product g Decision Variable = (( . 5 7!0. 2. where i and j corresponds to the machine product. [ * #* 3 = 1.( . [ *. [ *# ∗ . For the production chain of AMI is to explain if optimal working with split production orders (lots of the same order) to meet delivery times set with the customer.…. [ * (1) Subject to -! [ 6! [ . 2. Model Formulation n_i = number jobs of type i = = ℎ (i. ! " "# ( = $ % C(i.….n_i P(i. … . [ 0 * # *.-! [ *. o The quality of the final product is constant.5. inventory quality and is easy to perform. For each production order is determined by the quantity. Review of production orders.02 7.08 6. 2. In the first case.10 1. Result We considered two scenarios with the data of table 1. Info time (in seconds) that an item remains in each section of the paint line. in which were two political programming to meet scheduled delivery time. time data are recorded below: Table 3.98666667 Total days: 3. or 3 Last Name Yet 2.98 2.No Author 1..6.99 . starts the production of each order according to their order of arrival.95 11. Case 1 No Order 1 1 1 2 2 2 3 3 4 Quantity 1000 650 800 1200 1000 500 1200 1000 900 Total hours: 29. color. Information production orders Consider the following information to four production orders: The paint change in the system takes for roughly 7200 seconds. Information of the respective delivery dates and number of units outstanding for each order at the beginning of the planning period. and delivery time and admission date. Job Pick up Cleaning Drying Painting Oven Take down Quality Input (Seg) 0 720 1825 2810 3285 4270 4479 Out (Seg) 1620 2605 3080 4065 4274 6279 3.10 9.748333333 Color (i) Red Green Black Black Blue White White Black Black Delivery time (d) 2 2 2 3 3 3 1 1 2 Admission date 1 1 1 2 2 2 2 2 3 Duration seg 14478 28606 42884 7478 21956 35934 7478 21956 7178 Total duration (h) 4. Table 1.91 2. No Order 1 1 1 2 2 2 3 3 4 Quantity 1000 650 800 1200 1000 500 1200 1000 900 Color (i) Red Green Black Black Blue White White Black Black Delivery time (d) 2 2 2 3 3 3 1 1 2 Admission date 1 1 1 2 2 2 2 2 3 Table 2.08 6. Total time consumed (Hours). it does minimize manufacturing downtime affecting production rates and promise to comply with customers. . 2. Review of production orders. Total time consumed (Hours). Conclusion The present investigation was able to determine the sequencing of jobs (tasks) in AMI production systems from available resources (machinery.26694444 Total days: 2. are considered but are grouped by color regardless of the order they belong but sorts its input to the production line with next delivery date.02 2.83 4. equipment. Grouping color Color Black White Green Red Blue Start 0. supplies.408368056 Black White Green Red Blue 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Figure 3. Case 2. materials.No Author 1. Case 1.22 Duration seg 17378 15178 7849 14478 14478 Duration hours 4.18 4.00 4. 4. With the above. Case 2 No Order 3 1 4 2 3 2 1 1 2 Quantity 1000 800 900 1200 1200 500 650 1000 1000 Color (i) Black Black Black Black White White Green Red Blue Delivery time (d) 1 2 2 3 1 3 2 2 3 Admission date 2 1 3 2 2 2 1 1 2 Table 5. or 3 Last Name Yet Order 1 Order 1 Order 1 Order 2 Order 2 Order 2 Order 3 Order 3 Order 4 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 Figure 2.02 4. the same production orders.22 2.18 4. For the second assessment case.02 Total hours: 19. facilities) for processing production orders. The results are reported below: Table 4.83 4. providing improved solutions without major investments in technology resources. SIPPER. Planeacion y control de la produccion. & RITZMAN. 4. 6 edition. 2.No Author 1. 2001. J. Thesis Industrial Engineering. editorial Thomson Learning. . The content of manufacturing strategy: An empirical study. G. Pearson Education. ROBERT L. Greg. KRAJEWSKI.74%. AQUILANO. 568. Dominguez Machuca. References 1. Page. GONZALO. 446. Santa fe de Bogota. M. l. Chile. Primera edicion. Fifth Edition. PEÑA. fractionation of production orders (following batch planning) can run jobs in less time with greater efficiency. 10. ALBORNOZ S. machinery and plant) and the increased productivity of the manufacturing line.R. Ruiz Jimenez. 2000. Madrid: Mc Graw Hill de Espain S. Fifth Edition. CHASE. VICTOR M. which brings benefits to AMI in use of resources manufacturing (manpower. Manufacturing and services. IVAN. Daniel. College textbooks Ediuno. & CLEVELAND. Garcia David. N. 2. Production and Operations Management. Formulation and solution of models Lots Sizing under Uncertainty by Redefining Variables Techniques. 2000. Valparaiso. infrastructure or knowledge management. Journal of operations management.C.J. GAITHER. late costs and times and sequence dependent setup. which reduces operating costs and increases the benefit corporate. 5. MEJIA. Organization of production engineering. Eighth Edition. Mexico. Editorial Prentice Hall. l. RENDER. 2000. Finally it can shown that the production strategies that are developed under flow shop techniques are useful when it comes to problems with work areas complete tasks that can be split. Mexico 2004. F. A. Universidad de los Andes.B. SCHROEDER. Mexico D. Barry. 3. 2006. Technical University Federico Santa Maria.A.. Colombia. 6. 131. R. 2000.. Operations management.A.G. or 3 Last Name Yet Furthermore. Bulfin. Mc Graw Hill. increasing productivity and reducing the delay. ANDERSON. Production and Operations Management. Eighth Edition. Page. Norman. 8. & Alvarez Gil. Mc Graw Hill. DE LA FUENTE.F. Programming and production lot sizing considering early termination costs... Operations management: strategic aspects. Industries Department. Principles of Operations Management. the company associated with this was an improvement in the yield of 35. 2000. Pag. 9. 7. FRAZIER. & JACOBS. Maria Jose. R. Strategy and analysis. Bogota.