Tekli Dakikalarda Kalıp Değiştirme Zeki Karar Destek Sistemi Ve Tekstil Sektöründe Uygulaması

dc.contributor.advisor Cebeci, Ufuk tr_TR
dc.contributor.author Kemalbay, Volkan tr_TR
dc.contributor.authorID 434005 tr_TR
dc.contributor.department Endüstri Mühendisliği tr_TR
dc.contributor.department Industrial Engineering en_US
dc.date 2012 tr_TR
dc.date.accessioned 2012-06-26 tr_TR
dc.date.accessioned 2015-06-18T16:49:44Z
dc.date.available 2015-06-18T16:49:44Z
dc.date.issued 2012-06-27 tr_TR
dc.description Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2012 tr_TR
dc.description Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2012 en_US
dc.description.abstract Günümüzde sadece daha fazla yatırım yapmak ya da bir alanda yeteri kadar tecrübe sahibi olmak üretici firmalara rekabet avantajı sağlamaya yetmemektedir. Bu mücadelede ön plana çıkmanın yolu mevcut işgücü, makine, malzeme ve süreçleri optimum kontrol etmekten geçmektedir. Globalleşen dünyada bu kontrol mekanizmasını sağlam bir şekilde kurmanın yolu bilgiyi etkin bir şekilde kullanmaktan geçer. Yalın üretim, üretime yük getiren tüm israflardan arınmayı hedef alan bir yaklaşımdır. Yalın üretim sistemi, müşteri talebini en az kaynakla, en kısa zamanda, en ucuza ve hatasız olarak karşılamayı hedefler. Bir diğer deyişle, sıfır hatalı, tam zamanında, küçük partiler halinde, yüksek çeşitlilikte üretim yapılmasına olanak sağlar. Yalın üretim tekniklerinden biri olan SMED, üretim süreçlerindeki kayıpları azaltmaya yönelik kullanılan etkin bir yöntemdir. Bu teknik sayesinde üretimi devam eden bir parçadan, bir diğer parçaya geçiş çok esnek bir şekilde olabilmektedir. Bu tekniğin temel amacı üretim hattında beklemelere sebep olan uzun hazırlık sürelerini tekli dakikalara düşürerek, üretimin hızlı bir şekilde başlamasını sağlayabilmektir. SMED tekniği sayesinde hızlı ve esnek bir yapıya sahip olan üretici firmalar küçük partiler halinde üretim yapma imkanına sahip olup müşteri isteklerine kısa süre içerisinde cevap verebilmektedirler. SMED tekniğinin üretimde daha etkin bir şekilde kullanılabilmesi için sistemin zeki hale getirilmesi gerekir. Karar verme sürecinin zeki olabilmesi için yapay zeka ile tasarlanmış bir uzman sistem kullanılması gerekmektedir. Uzman sistemler bulanık yapay sinir ağları veya genetik algoritma kullanır. Ancak SMED tekniğinin insan gibi düşünmesi için uzman sistemin yapay sinir ağları içermesi gerekir. Çünkü mevcut olan kuralların yerine yeni kurallar gelmesi durumunda sistemin bunu öğrenmesi gerekir. SMED’te yapay zekayı ve yapay bilinci oluşturmak için çeşitli türde neronlar vardır. Bu neronlar ise bilgiyi yapay sinir ağlarının düğüm ve yolları ile uzman sistemlere aktarırlar. Böylece sistem bu düğüm ve yolları kullanarak öğrenme gerçekleştirir. Bu çalışma 7 bölümden oluşmaktadır. Birinci bölümde tezin amacından bahsedilmiş ve bu konu üzerinde yazılmış olan bilimsel kaynaklardan oluşan literatür araştırması hakkında bilgi verilmiştir. Çalışmanın ikinci bölümünde yalın üretim sisteminden detaylı bir şekilde bahsedilmiş ve bazı yalın üretim tekniklerinden tam zamanlı üretim, kanban sistemi ve 5S tekniğinin üretim açısından önemi anlatılmıştır. Üçüncü bölümde ise yalın üretim tekniklerinden biri olan SMED detaylı bir şekilde ele alınmıştır. Dördüncü bölümde ise karar destek sistemleri hakkında geniş bilgiler verilmiştir. Beşinci bölümde bilgi türleri belirlenerek SMED için veritabanı yönetimi oluşturulmuştur. Daha sonra ise SMED zeki karar destek sistemi kurulup tekstil sektörü için kurallar çıkarttırılmıştır. Çalışmanın altıncı bölümünde ise perde komponentleri üreten bir firmanın üretim hattında SMED teknikleri uygulanarak üretim sistemi verimli hale getirilip belirlenen kuralların bir kısmı firmaya zeki karar destek sistemi ile entegre edilmiştir. Son bölümde ise zeki karar destek sisteminin SMED’e olan etkileri ve ileride gerçekleşmesi mümkün olacak durumlar anlatıldı. tr_TR
dc.description.abstract Today more investment or having enough experience in an area is not sufficient for companies to provide a competitive advantage. The way to come to the fore in this competition is based on optimum control of existing workforce, machine, material and processes. In the globalizing world the way of establishing this mechanism on robust mean depends on effective use of information. Lean manufacturing is an approach aimed at cleansing all wastes that is causing burden. Lean manufacturing system aims to meet customer demands with least amount of source, in the shortest time, with the cheapest and without an error. In other words it enables just in time and high variety manufacturing in small lots with zero defects. As one of the lean manufacturing technique SMED is an effective method to reduce losses in the manufacturing process. By virtue of this technique changeover from a piece which is in manufacturing process to other piece can be very smooth and flexible. The main purpose of the technique is to reduce set up time single minutes that causes waiting on production line and is to provide a quick way to start manufacturing. With SMED technique, manufacturers with a fast and flexible structure can be capable of producing in small lots and can be able to give quick responses to customer demands in short time. SMED technique can be used more effectively in production it is necessary the implementation of intelligent systems. To make the decision making process intelligent an expert system designed with artificial intelligence is required to be used. However thinking of SMED technique as human being expert system must contain artificial neural network. Because in the case of replacement of existing rules with new rules, the system should be able to learn it. At this point nodes and paths of artificial neural networks take in charge. Artificial intelligence that purpose the long-term goal of simulating the human brain in real time and describe artificial consciousness, is a structure. Using nodes and paths of artificial neural networks, this structure redound the ability of intelligent decision making for creating questions and rules of SMED. Additionally, artificial intelligence has simulating neurons, visualizing neurons and knowledge acquisition neurons. However, expert system is computer programs called artificial intelligence. This study consists of seven chapters. In the first chapter aim of the study is specified and literature review from published scientific works related to this topic is mentioned. At the second chapter of the study the lean manufacturing system is mentioned in detail and as some of the lean manufacturing techniques: just in time production, kanban system and importance of 5S technique is described in terms of production. If it is necessary to explain all these techniques, Just-in-time production is a strategy used in the production industry to reduce costs by reducing the in-process inventory level. It is driven by a series of signals that tell the production line to make the next piece for the product and when it is needed. The signals used are usually simple visual signals, such as the absence or presence of a piece that is needed in the production process. In other words, it means having right part at the right place in the right amount at the right time. Kanban is an information system which is used to control the flow of production and material. Hereby, it could be controlled whole processes of production that are which having right part at the right place in the right amount at the right time. 5S is list describes how to organize a shop floor for efficiency and effectiveness by identifying and storing the materials used, maintaining the area and materials, and sustaining the new order. At the third chapter as one of the lean manufacturing technique SMED is discussed in detail. It is mentioned in that part about the fundamentals of SMED, its stages and its’ principles. In the first stage of SMED is separation of internal set-ups and external set-ups i.e. separation of processes while machine is not running and whilst machine is running. Certain tasks can frankly be done before machines are off for changeover. For example it could be done stand ready of operator, preparing parts and tools, making repairs, bringing the parts and tools closer to the working area by using checklists, performing functions checks and improving transport of dies and other tools. For the second stage internal set-ups are converted to external set-ups i.e. the processes when the machine is stopped could be carried out converted to the processes when the machine is operating. It is carried out with two steps, first step is to look the right functions and goals of each process in the existing internal setup. Other one is to find methods to convert these internal setup processes to external setup by several techniques such as; preparing operating conditions in advance, standardizing required functions and using intermediary jigs. For the last stage both internal and external set-ups are observed every detail via implementation of parallel operations, usage of functional clamps, elimination of adjusting procedures, mechanization, keep ready the dies and the usage of colour factor. In the fourth chapter expanded information is given about decision support systems. In addition as one of the decision support system, knowledge-driven decision support system i.e. intelligent decision support system structure, types, advantages and disadvantages are given in detailed information. A decision support system is a computer-based information system that supports business or organizational decisions and activities. The decision support system serve the management, operations, and planning levels of an organization and help to make decisions, which could be rapidly changing and not easily specified in advance. So the decision support system requires a hierarchic approach. Such a framework that includes people, technology, and the development approach. Used by the decision support system, the expert system gathers and presents typical information such as inventories of information assets that include relational data sources and data warehouses. It has technology levels for using hardware and software. The first of these is the actual application that will be used by the users. Other one is its tool that includes lower level hardware/software. A decision support system may present information graphically and may include an expert system and artificial intelligence. These can be categorized into five types; model-driven DSS, data-driven DSS, knowledge-driven DSS, communications-driven DSS, document-driven DSS. The model-driven DSS is used to query a database or data warehouse to seek specific answers for specific purposes. These are sent out via a client/server link or via the web. The document-driven DSS are targeted to reach broad base of user. The knowledge-driven DSS is used expert technology that has server systems, the web and sofware. The model-driven DSS are complex systems that help analyse decisions or choose between different options. The communications-driven DSS are targetted at internal teams, including partners. Its purpose are to help conduct a meeting or for users to collaborate. In the fifth chapter thereby determining knowledge type database management system is created. The function of artificial intelligence is explicated at intelligent decision support system and after that expert system is used at intelligent decision support system thus the relationship with SMED is intended to show. After established system is explained with respect to how to improve. To sum up, considering relationship between SMED and intelligent decision support system, on the sector of thesis work implemented specific questions are asked. According to the received responses certain rules are created at the structure of if then. In this way the system had the ability to learn from its own experiences and became capable of making decisions based on these experiences. Thus the system became capable of giving suggestions and come up with solutions so make decisions like a human being with the ability of comparing the information it has. At the sixth chapter of the study it is mentioned the company where the study implemented. After then this to figure out one of the most important bottlenecks in the production line SMED study was carried out towards the elimination of set-up times. In order to achieve purpose of this study a SMED study team identified. Thereafter for the machine that creates bottleneck at the existing production line which is predetermined, improvements have been completed to the most frequently changed die with the team of SMED. The results of the improvement works described in comparison to the former situation. Also to accomplish the goal of exchange of die in single minutes, electro-magnetic system which designed according to technical specifications of existing machinery and dies thus started to the method of changeover the die. In this way targeted single minute exchange of die is accomplished. On the other hand, kanban calculations are made which is the other technique of lean manufacturing for the chosen product to define the necessary kanban amount. In this way, after the implementation of SMED and kanban technique was indicative of interaction with each other. As a result by courtesy of decreasing set-up times, the company after the improvements of SMED have had the opportunity to make small lots of production with its degraded lower level of stocks thus the company had a new structure so with its new structure became able to give quick response to customers’ requirements in an efficient way. Beside at the previous chapter SMED rules identified for the sector to intelligent decision support system and question rule flow diagrams are created. Thus, how much of these rules could be implemented was shown in the company. At the final chapter, it is explained results and evaluations of the thesis work clearly and is expressed the original point of the intelligence decison support system which is established in comparison with other systems. Additionally , it is given some suggestions for further research which could be used by who wants to improve this study with another aspects. Today more investment or having enough experience in an area is not sufficient for companies to provide a competitive advantage. The way to come to the fore in this competition is based on optimum control of existing workforce, machine, material and processes. In the globalizing world the way of establishing this mechanism on robust mean depends on effective use of information. Lean manufacturing is an approach aimed at cleansing all wastes that is causing burden. Lean manufacturing system aims to meet customer demands with least amount of source, in the shortest time, with the cheapest and without an error. In other words it enables just in time and high variety manufacturing in small lots with zero defects. As one of the lean manufacturing technique SMED is an effective method to reduce losses in the manufacturing process. By virtue of this technique changeover from a piece which is in manufacturing process to other piece can be very smooth and flexible. The main purpose of the technique is to reduce set up time single minutes that causes waiting on production line and is to provide a quick way to start manufacturing. With SMED technique, manufacturers with a fast and flexible structure can be capable of producing in small lots and can be able to give quick responses to customer demands in short time. SMED technique can be used more effectively in production it is necessary the implementation of intelligent systems. To make the decision making process intelligent an expert system designed with artificial intelligence is required to be used. However thinking of SMED technique as human being expert system must contain artificial neural network. Because in the case of replacement of existing rules with new rules, the system should be able to learn it. At this point nodes and paths of artificial neural networks take in charge. Artificial intelligence that purpose the long-term goal of simulating the human brain in real time and describe artificial consciousness, is a structure. Using nodes and paths of artificial neural networks, this structure redound the ability of intelligent decision making for creating questions and rules of SMED. Additionally, artificial intelligence has simulating neurons, visualizing neurons and knowledge acquisition neurons. However, expert system is computer programs called artificial intelligence. This study consists of seven chapters. In the first chapter aim of the study is specified and literature review from published scientific works related to this topic is mentioned. At the second chapter of the study the lean manufacturing system is mentioned in detail and as some of the lean manufacturing techniques: just in time production, kanban system and importance of 5S technique is described in terms of production. If it is necessary to explain all these techniques, Just-in-time production is a strategy used in the production industry to reduce costs by reducing the in-process inventory level. It is driven by a series of signals that tell the production line to make the next piece for the product and when it is needed. The signals used are usually simple visual signals, such as the absence or presence of a piece that is needed in the production process. In other words, it means having right part at the right place in the right amount at the right time. Kanban is an information system which is used to control the flow of production and material. Hereby, it could be controlled whole processes of production that are which having right part at the right place in the right amount at the right time. 5S is list describes how to organize a shop floor for efficiency and effectiveness by identifying and storing the materials used, maintaining the area and materials, and sustaining the new order. At the third chapter as one of the lean manufacturing technique SMED is discussed in detail. It is mentioned in that part about the fundamentals of SMED, its stages and its’ principles. In the first stage of SMED is separation of internal set-ups and external set-ups i.e. separation of processes while machine is not running and whilst machine is running. Certain tasks can frankly be done before machines are off for changeover. For example it could be done stand ready of operator, preparing parts and tools, making repairs, bringing the parts and tools closer to the working area by using checklists, performing functions checks and improving transport of dies and other tools. For the second stage internal set-ups are converted to external set-ups i.e. the processes when the machine is stopped could be carried out converted to the processes when the machine is operating. It is carried out with two steps, first step is to look the right functions and goals of each process in the existing internal setup. Other one is to find methods to convert these internal setup processes to external setup by several techniques such as; preparing operating conditions in advance, standardizing required functions and using intermediary jigs. For the last stage both internal and external set-ups are observed every detail via implementation of parallel operations, usage of functional clamps, elimination of adjusting procedures, mechanization, keep ready the dies and the usage of colour factor. In the fourth chapter expanded information is given about decision support systems. In addition as one of the decision support system, knowledge-driven decision support system i.e. intelligent decision support system structure, types, advantages and disadvantages are given in detailed information. A decision support system is a computer-based information system that supports business or organizational decisions and activities. The decision support system serve the management, operations, and planning levels of an organization and help to make decisions, which could be rapidly changing and not easily specified in advance. So the decision support system requires a hierarchic approach. Such a framework that includes people, technology, and the development approach. Used by the decision support system, the expert system gathers and presents typical information such as inventories of information assets that include relational data sources and data warehouses. It has technology levels for using hardware and software. The first of these is the actual application that will be used by the users. Other one is its tool that includes lower level hardware/software. A decision support system may present information graphically and may include an expert system and artificial intelligence. These can be categorized into five types; model-driven DSS, data-driven DSS, knowledge-driven DSS, communications-driven DSS, document-driven DSS. The model-driven DSS is used to query a database or data warehouse to seek specific answers for specific purposes. These are sent out via a client/server link or via the web. The document-driven DSS are targeted to reach broad base of user. The knowledge-driven DSS is used expert technology that has server systems, the web and sofware. The model-driven DSS are complex systems that help analyse decisions or choose between different options. The communications-driven DSS are targetted at internal teams, including partners. Its purpose are to help conduct a meeting or for users to collaborate. In the fifth chapter thereby determining knowledge type database management system is created. The function of artificial intelligence is explicated at intelligent decision support system and after that expert system is used at intelligent decision support system thus the relationship with SMED is intended to show. After established system is explained with respect to how to improve. To sum up, considering relationship between SMED and intelligent decision support system, on the sector of thesis work implemented specific questions are asked. According to the received responses certain rules are created at the structure of if then. In this way the system had the ability to learn from its own experiences and became capable of making decisions based on these experiences. Thus the system became capable of giving suggestions and come up with solutions so make decisions like a human being with the ability of comparing the information it has. At the sixth chapter of the study it is mentioned the company where the study implemented. After then this to figure out one of the most important bottlenecks in the production line SMED study was carried out towards the elimination of set-up times. In order to achieve purpose of this study a SMED study team identified. Thereafter for the machine that creates bottleneck at the existing production line which is predetermined, improvements have been completed to the most frequently changed die with the team of SMED. The results of the improvement works described in comparison to the former situation. Also to accomplish the goal of exchange of die in single minutes, electro-magnetic system which designed according to technical specifications of existing machinery and dies thus started to the method of changeover the die. In this way targeted single minute exchange of die is accomplished. On the other hand, kanban calculations are made which is the other technique of lean manufacturing for the chosen product to define the necessary kanban amount. In this way, after the implementation of SMED and kanban technique was indicative of interaction with each other. As a result by courtesy of decreasing set-up times, the company after the improvements of SMED have had the opportunity to make small lots of production with its degraded lower level of stocks thus the company had a new structure so with its new structure became able to give quick response to customers’ requirements in an efficient way. Beside at the previous chapter SMED rules identified for the sector to intelligent decision support system and question rule flow diagrams are created. Thus, how much of these rules could be implemented was shown in the company. At the final chapter, it is explained results and evaluations of the thesis work clearly and is expressed the original point of the intelligence decison support system which is established in comparison with other systems. Additionally , it is given some suggestions for further research which could be used by who wants to improve this study with another aspects. en_US
dc.description.degree Yüksek Lisans tr_TR
dc.description.degree M.Sc. en_US
dc.identifier.uri http://hdl.handle.net/11527/5780
dc.publisher Fen Bilimleri Enstitüsü tr_TR
dc.publisher Institute of Science and Technology en_US
dc.rights İTÜ tezleri telif hakkı ile korunmaktadır. Bunlar, bu kaynak üzerinden herhangi bir amaçla görüntülenebilir, ancak yazılı izin alınmadan herhangi bir biçimde yeniden oluşturulması veya dağıtılması yasaklanmıştır. tr_TR
dc.rights İTÜ theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. en_US
dc.subject yalın üretim tr_TR
dc.subject tekli dakikalarda kalıp değiştirme tr_TR
dc.subject zeki karar destek sistemi tr_TR
dc.subject lean manufacturing en_US
dc.subject smed en_US
dc.subject intelligent decision support system en_US
dc.title Tekli Dakikalarda Kalıp Değiştirme Zeki Karar Destek Sistemi Ve Tekstil Sektöründe Uygulaması tr_TR
dc.title.alternative Single Minute Exchange Of Die - Intelligent Decision Support System - Application Of Smed Into Textile Industry en_US
dc.type Thesis en_US
dc.type Tez tr_TR
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