Penjadwalan Produksi Menggunakan Metode Simulated Annealing pada Unit Produksi Daun Pintu di PT. ML

Author(s):  
Rosnani Ginting ◽  
Chairul Rahmadsyah Manik

Penjadwalan merupakan aspek yang sangat penting karena didalamnya terdapat elemen perencanaan dan pengendalian produksi bagi suatu perusahaan yang dapat mengirim barang sesuai dengan waktu yang telah ditentukan, untuk memperoleh waktu total penyelesaian yang minimum. Masalah utama yang dihadapi oleh PT. ML adalah keterlambatan penyelesaian order yang mempengaruhi delivery time ke tangan costumer karena pelaksanaan penjadwalan produksi dilantai pabrik belum menghasilkan makespan yang sesuai dengan order yang ada. Oleh kaena itu dituntut untuk mencari solusi pemecahan masalah optimal dalam penentuan jadwal produksi untuk meminimisasi total waktu penyelessaian (makespan) semua order. Dalam penelitian ini, penjadwalan menggunakan metode Simulated Annealing (SA) diharapkan dapat menghasilkan waktu total penyelesaian lebih cepat dari penjadwalan yang ada pada perusahaan.   Scheduling is a very important aspect because in it there are elements of planning and production control for a company that can send goods in accordance with a predetermined time, to obtain a minimum total time of completion. The main problem faced by PT. ML is the delay in completing orders that affect delivery time to customer because the implementation of production scheduling on the factory floor has not produced the makespan that matches the existing order. Therefore, it is required to find optimal problem solving solutions in determining the production schedule to minimize the total time of elimination (makespan) of all orders. In this study, scheduling using the Simulated Annealing (SA) method is expected to produce a total time of completion faster than the existing scheduling in the company.

2019 ◽  
Vol 2 (2) ◽  
pp. 44-51
Author(s):  
Kania Kania ◽  
Ely Nuryani ◽  
Azwarsyah Azwarsyah

Design of production and delivery monitoring applications at PT. Indah Kiat Pulp & Paper Serang Mill Tbk aims to reduce problems in the production control process. The problems faced are as follows; the production process carried out by several parts results in slow processing of products, often duplicate data orders that can harm the company, the production of damaged products is not recorded, the number of reprimands from customers due to delay in delivery time due to ordering deficiencies the company must reset the production schedule. Based on these problems computer-based method (IT) shortage is needed. System design uses the waterfall method or SDLC (System Development Life Cycle). Software modeling uses UML (unified model language). The application has advantages such as the more structured and well-documented because the procedure is in accordance with the rules made by the Converting Division at PT. Indah Kiat Pulp & Paper. This application is expected to be able to overcome all existing constraints, especially in managing production data. Based on the things mentioned above, the authors are interested in compiling articles about the design of Production and Delivery Monitoring Applications with the Shortage Method at PT. Indah Kiat Pulp & Paper Serang Mill Tbk.


2012 ◽  
Vol 13 (1) ◽  
pp. 51
Author(s):  
Iffan Maflahah ◽  
Machfud Machfud ◽  
Faqih Udin

Planning and production control are important factors to determine the efficiency derived through proper managementof raw material supply of fresh fruits, production planning and master production schedule. This research aimed to developthe aggregate production planning model, and master production schedule model for juice production from fresh fruit, while also considered the perishability of the fresh fruit. There were several methods applied in the works, namely autoregressive integrated moving average (ARIMA) for forecasting of raw material product sale, mathematical model for raw material supply, linear programming for production planning and prospective production scheduling to develop master production schedule. This research developed software for decision support system called RP_JUS. The results showed that all raw material damage was distributed exponentially. Decision Support Model of Production Schedule for Fresh Fruit Juice can be applied to the processing indudtries that use fresh fruit.


2012 ◽  
Vol 468-471 ◽  
pp. 2661-2667
Author(s):  
Ya Zhou Chen ◽  
Lin Wang

Based on the analyzing of the characteristics of a Body-In-White pressing production process a pressing workshop production management system has been given in order to make the ERP production scheduling more executable. The detailed function model of it such as task assignment, quality control, mold maintenance and production scheduling has been thoroughly discussed. In order to make the production line capability balance the task dispatching algorithm has been given and the dynamic dispatching and controlling process has been explained. This system can be integrated with the upper ERP/CAPP/PDM system which can improve the information level of a company.


Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1126
Author(s):  
Marta Lilia Eraña-Díaz ◽  
Marco Antonio Cruz-Chávez ◽  
Fredy Juárez-Pérez ◽  
Juana Enriquez-Urbano ◽  
Rafael Rivera-López ◽  
...  

This paper presents a methodological scheme to obtain the maximum benefit in occupational health by attending to psychosocial risk factors in a company. This scheme is based on selecting an optimal subset of psychosocial risk factors, considering the departments’ budget in a company as problem constraints. This methodology can be summarized in three steps: First, psychosocial risk factors in the company are identified and weighted, applying several instruments recommended by business regulations. Next, a mathematical model is built using the identified psychosocial risk factors information and the company budget for risk factors attention. This model represents the psychosocial risk optimization problem as a Multidimensional Knapsack Problem (MKP). Finally, since Multidimensional Knapsack Problem is NP-hard, one simulated annealing algorithm is applied to find a near-optimal subset of factors maximizing the psychosocial risk care level. This subset is according to the budgets assigned for each of the company’s departments. The proposed methodology is detailed using a case of study, and thirty instances of the Multidimensional Knapsack Problem are tested, and the results are interpreted under psychosocial risk problems to evaluate the simulated annealing algorithm’s performance (efficiency and efficacy) in solving these optimization problems. This evaluation shows that the proposed methodology can be used for the attention of psychosocial risk factors in real companies’ cases.


2012 ◽  
Vol 190-191 ◽  
pp. 156-159
Author(s):  
Jian Qing Chen

This paper is under the research background of a switch machine production enterprise informatization projects, and the production schedule is mainly based on customer orders and sales forecasts. This paper mainly studies the combination of similar order processing sheets according to the similarity of types and specifications of products in an order processing sheet, and the experience of master production scheduling personnel, to generate the master production scheduling methods and techniques. Finally, studies the material requirements planning methods based on nested components, focusing on the configuration of parts and components of such products in the product configuration.


Impact ◽  
2020 ◽  
Vol 2020 (8) ◽  
pp. 60-61
Author(s):  
Wei Weng

For a production system, 'scheduling' aims to find out which machine/worker processes which job at what time to produce the best result for user-set objectives, such as minimising the total cost. Finding the optimal solution to a large scheduling problem, however, is extremely time consuming due to the high complexity. To reduce this time to one instance, Dr Wei Weng, from the Institute of Liberal Arts and Science, Kanazawa University in Japan, is leading research projects on developing online scheduling and control systems that provide near-optimal solutions in real time, even for large production systems. In her system, a large scheduling problem will be solved as distributed small problems and information of jobs and machines is collected online to provide results instantly. This will bring two big changes: 1. Large scheduling problems, for which it tends to take days to reach the optimal solution, will be solved instantly by reaching near-optimal solutions; 2. Rescheduling, which is still difficult to be made in real time by optimization algorithms, will be completed instantly in case some urgent jobs arrive or some scheduled jobs need to be changed or cancelled during production. The projects have great potential in raising efficiency of scheduling and production control in future smart industry and enabling achieving lower costs, higher productivity and better customer service.


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Inna Kholidasari ◽  

Production scheduling is the most important part in carrying out the production process that will be carried out on a production floor. Scheduling activities are carried out before the production process begins to ensure the smooth running of the production process. If the production scheduling is not done properly, there will be obstacles in the production process and will cause losses to the company. This study aims to determine the production machine scheduling in a company engaged in the manufacture of spare parts for automotive products. This company implements a job shop production process and uses the First In First Out method in completing its work. Due to the large number of products that have to be produced, there are often two or more products that must be worked on at the same time and machine. This condition causes some products to have to wait for the associated machine to finish operating and causes long product turnaround times. This problem is solved by making a production machine scheduling using the Non-Delay method. By applying this method, the makespan of completion time can be minimized.


Author(s):  
António Santos Marques ◽  
Nelson Chibeles-Martins ◽  
Tânia Pinto-Varela

2018 ◽  
Vol 66 (11) ◽  
pp. 950-963 ◽  
Author(s):  
Egidio Leo ◽  
Sebastian Engell

Abstract For the optimal operation of power-intensive plants, a challenge which is addressed in this work is to simultaneously determine the optimal production schedule and the optimal day-ahead electricity commitment. In order to ensure stability of the power grid, the electricity suppliers impose a daily electricity commitment to large consumers. The consumers have to commit one day in advance to the amount of energy they are going to purchase and use for a horizon of 24 hours (with an hourly discretization) and in case the actual electricity consumption differs significantly from the committed profile, the consumer is obliged to pay penalties. Since the consumers have to commit to the electricity suppliers before the actual electricity demand is known, uncertainty needs to be taken into account. A stochastic mixed-integer linear programming model is developed to consider two critical sources of uncertainty: equipment breakdowns and deviation prices. Equipment breakdowns can reduce the production capacity and make the actual electricity consumption deviate from the day-ahead electricity commitment. The application of the proposed approach to a continuous power-intensive plant shows the benefit gained from the solution of the stochastic model instead of the deterministic counterpart in terms of reduction of the cost of the energy.


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