Residual Based Flow Time Estimation Algorithm for Labor Intensive Project Type Production Systems

Karaoğlan, Aslan Deniz

doi:10.21205/deufmd.2016185423

Cited by 3 publications

(3 citation statements)

References 21 publications

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“…Ardından tasarlanan deneyin ölçülen çıktılarına göre, girdilerle çıktılar arasındaki matematiksel ilişkiyi gösteren regresyon modeli kurularak eniyileme yapılabilir. YYY'nin matematiksel modelinin genel gösterimi Denklem (1)'de verildiği gibidir [11]- [14]:…”

Section: Materyal Ve Metot 21 Yanıt Yüzey Yöntemi (Yyy)unclassified

Minimization of pres time at particleboard production

Karaoğlan¹,

Demir²,

Çarkacı³

2018

Pamukkale J Eng Sci

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Dünyada yonga levha üretiminde yaşanan yoğun rekabet, maliyetler üzerinde etkili önemli parametrelerden biri olan işlem sürelerinin enküçüklenmesini zorunlu kılmaktadır. Bu çalışmada, deney tasarımı tekniklerinden yaygın olarak kullanılan yanıt yüzey yöntemi (YYY)'nin matematiksel alt yapısı kullanılarak, üretim hızını arttırmak amacıyla pres süresinin enküçüklenmesi amaçlanmıştır. Bu amaçla yonga levhanın pres süresi üzerinde etkili değişkenlerden; yonga levhanın rutubeti, banyo jeli süresi, yonga levhanın altı için gravür jeli süresi, yonga levhanın üstü için gravür jeli süresi, akış, final ağırlığı, kağıdın rutubeti, üreformaldehit (UF) miktarı, melamin formaldehit (MF) miktarı, pres yoğunluğu, pres basıncı ve pres sıcaklığı girdilerinin optimum değerleri araştırılmıştır. Bu sayede pres süresi azaltılırken, üretim miktarı ve hattın verimliliğinin arttırılması amaçlanmıştır. Modelleme amacıyla, her biri 5 tekrarlı 56 tane gözlem değeri kullanılarak girdilerle pres süresi arasındaki matematiksel ilişki belirlenmiş ve ardından eniyileme yapılmıştır. Çalışmanın sonunda, hali hazırda seçilen ürün tipi için gözlenen en düşük pres süresi olan 13.57 sn. 11 sn. kadar düşürülmüştür. The intense competition in the production of particleboard in the world requires minimization of process times which is one of the important parameters effective on costs. In this study, it is aimed to minimize the press time in order to increase the production speed by using the mathematical sub-structure of the response surface method (RSM) which is one of the well-known design of experiments techniques. For this purpose, optimum levels of the factors those have effect on press time namely humidity of the particleboard, bath gel time, gravure gel time for the bottom of the particleboard, gravure gel time for the top of the particleboard, flow, final weight, humidity of the paper, amount of urea-formaldehyde (UF), amount of melamine formaldehyde (MF), press density, press pressure and press temperature were investigated. In this case, It is aimed to increase the production amount and productivity of the line while decreasing the press time. For the purpose of modeling, the mathematical relationship between the factors and the press time was determined by using 56 observation values of 5 repetitions each and then optimization was performed. At the end of the study, the press time is reduced to 11 seconds from 13.57 seconds-which is the lowest press time observed for the currently selected item type.

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Section: Materyal Ve Metot 21 Yanıt Yüzey Yöntemi (Yyy)unclassified

Minimization of pres time at particleboard production

Karaoğlan¹,

Demir²,

Çarkacı³

2018

Pamukkale J Eng Sci

Self Cite

View full text Add to dashboard Cite

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“…In the labor intensive project type manufacturing; except a few similar orders produced frequently; there are unlimited types of different orders varying based on the technical specifications demanded by the customers and the state of the shop floor is changed continuously. This variation causes unknown processing times for each type of order which makes order scheduling harder [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Scheduling Customized Orders by Considering the Ergonomic Constraints: A Case Study at YEMTAR Company

Karaoğlan¹,

Ocaktan²,

Gönen³

et al. 2018

World Congress on Mechanical, Chemical, and Material Engineering

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It is important for companies to meet customer demands by due date and reduce the labor cost on the finalized product. For this purpose, order scheduling is required for different purposes such as minimizing makespan, maximizing resource utilization, etc. Dynamic production environment causes stochastic operation times at companies which work based on project type labor-intensive production. Stochastic operation times make order scheduling harder. There are many reasons that causes operation times being stochastic such as technical specifications of the orders, skills of the operators, bottlenecks in the job-shop, and etc. However, one of the most important but less discussed constraints that affect the probability distribution of the operation times is the ergonomic constraint. Ergonomic constraints, such as musculoskeletal discomfort, fatigue and limitations determined by the laws make it even more difficult to predict the total makespan of waiting orders. In this study, an order scheduling algorithm that considers the dynamical production environment and the ergonomic limitations is proposed for nearly optimizing average makespan for several waiting orders in the grinding and painting workstation of YEMTAR Company. The proposed algorithm adopts the technical order specifications and ergonomic constraints together, computes the stochastic operation times by using simulation, and schedule orders by using genetic algorithm. The objective is to determine the entry sequence of the waiting orders to the workshop for minimizing their average makespan which directly influences the resource utilization, efficiency, and labor costs.

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“…Except a few similar transformers produced frequently; there are unlimited types of different transformer orders varying based on the technical specifications demanded by the customers for those to be produced for the first time. This variation causes considerable amount of differences in processing times, makespan and due date for each type of order which are unknown and must be predicted before starting the production [2][3][4]. For this purpose, an effective scheduling is required for minimizing the labor cost and due date.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Customized Orders: A Case Study at BEST Transformers Company

Ocaktan¹,

Küçükkoç²,

Karaoğlan³

et al. 2017

World Congress on Mechanical, Chemical, and Material Engineering

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-Stochastic operation times make job-shop scheduling harder at companies which work based on project type laborintensive production in a dynamic environment. The operation times are not known before production and change based on the orders' technical specifications. In performing required operations with the aim of producing a final product, scheduling is required for different purposes such as minimizing makespan, maximizing resource utilization, etc. This is important as it enables companies to meet customer demands by due date and reduce the labor cost on the finalized product. In this study, an order scheduling algorithm is proposed for nearly optimizing average makespan for several waiting orders in a transformer company's core production workshop considering dynamical production environment. The proposed algorithm adopts the technical order specifications, computes the stochastic operation times making use of simulation, and schedule orders using one of the widely used meta-heuristics, namely genetic algorithm. The objective is to determine the entry sequence of the waiting orders to the core production workshop for minimizing their average makespan which directly influences the resource utilization, efficiency, and labor costs.

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Residual Based Flow Time Estimation Algorithm for Labor Intensive Project Type Production Systems

Cited by 3 publications

References 21 publications

Minimization of pres time at particleboard production

Minimization of pres time at particleboard production

Scheduling Customized Orders by Considering the Ergonomic Constraints: A Case Study at YEMTAR Company

Scheduling Customized Orders: A Case Study at BEST Transformers Company

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