Toplam kalite yöntemi, istatiksel süreç kontrolü ve Türk metal sanayiinde kullanımları
Başlık çevirisi mevcut değil.
- Tez No: 55655
- Danışmanlar: PROF.DR. M. NİHAT SERASLAN
- Tez Türü: Yüksek Lisans
- Konular: Endüstri ve Endüstri Mühendisliği, Industrial and Industrial Engineering
- Anahtar Kelimeler: Belirtilmemiş.
- Yıl: 1996
- Dil: Türkçe
- Üniversite: İstanbul Teknik Üniversitesi
- Enstitü: Fen Bilimleri Enstitüsü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: 126
Özet
ÖZET Gerek iç ve gerekse dış pazarlarda giderek rekabeti daha yoğun bir biçimde hisseden imalatçı firmalar için kalite yönetimi yaşamsal önem kazanmaktadır. Yüksek kalite düzeylerine, verimlilikten de fedakarlık etmeden ulaşabilmenin yolu, hataları oluşmadan önleyebilmek ve hataları önceden tahmin edip tedbirlerini almaktan geçer Üretim sürecinde geleneksel yaklaşım, üretim biriminin bir ürünü üretmesi, kalite kontrol bölümünün ise bunları müşteriye sevk etmeden önce, istenilen ölçülere uymayan, hatalı ürünleri ayıklamasıdır. Üretim sisteminin hatalı ürünler de üretebileceğini kabul eden her kuruluş, bunların tüketiciye gitmesini önlemek amacıyla bir ayıklama sistemi kurmak zorundadır. Bu ayıklama sistemindeki çeşitli kontrol ve testler, hatalı ürünleri“iç hatalar”olarak ayırır. Bunlar atılacak, yeniden kontrol edilecek, düzeltilecek veya yeniden üretilecek ürünlerdir. Ancak ayırma işlemi güvenilirliği yüksek olan bir işlem değildir. Süzgeçten kaçarak tüketiciye kadar giden“dış hatalar”, şikayete konu olmakta, iade edilmekte, tazminat talepleri doğurmakta ve sipariş veya müşteri kaybına neden olabilmektedir. Dış hatalara karşı duyarlı olan bir kuruluş, kontrolü sıkılaştırarak dış hataları azaltabilmekte, ancak doğal olarak iç hataları aynı oranda artırmaktadır.“Ayırma”işleminin“önleme”işlemi ile yer değiştirdiği farklı bir yaklaşımla iç ve dış hataları birlikte azaltmak mümkündür. Böyle bir yaklaşımda süreç ve girdilerin daha iyi kontrolü ile hatalar oluşmadan önlem alınmaktadır. Bu noktada İstatistiksel Süreç Kontrolünün önemi anlaşılmaktadır. En uygun kaliteyi oluşturma çabalan, işletmede, sürekli olarak süreç geliştirmeyi ve denetimi zorunlu kılmaktadır. Sürekli olarak artan ve yükselen müşteri beklentilerinden daha hızlı bir kalite ve verim geliştirme hızı sağlayabilen bir kuruluş, rekabet gücü kazanmakta ve pazarda başarıya ulaşmaktadır. Bu kadar büyük öneme sahip kalite konularında kullanılan istatistiksel yöntemler konusunda, MESS'e bağlı işletmelerin bulunduktan durum hakkında bilgi edinmek amacıyla, bir anket çalışması düzenlenmiştir. En doğru cevapların alınabilmesi için, anketi dolduran kişilerin kalite kontrol konusunda en üst düzeyde bir unvana sahip olmalanna özen gösterilmiştir. Ankete verilen tüm yanıtlar, sayısal değerlere dönüştürüldükten sonra, SPSS for Windows istatistik paket programı ile sıklıklar, korelasyonlar ve ikili ilişkiler bakımından incelenmiş ve kalite konulan üzerine yapılan literatür araştırması sırasında elde edilen bilgilerle anket değerleri yorumlanmaya çalışılmıştır.
Özet (Çeviri)
SUMMARY TOTAL QUALITY MANAGEMENT, STATISTICAL PROCESS CONTROL AND THEIR APPLICATIONS IN TURKISH METAL WORKING INDUSTRY Before talking in terms of quality, one must describe what quality is. A search for the definition of quality has yielded inconsistent results. Quality has been variously defined as;“Value (Abbott, 1955; Feigenbaum, 1951) Conformance to specifications (Gilmore, 1974; Levitt, 1972), Conformance to requirements (Crosby, 1979), Fitness for use (Juran, 1974, 1988), Loss avoidance (Taguchi, cited in Ross, 1989), and Meeting and/or exceeding customers' expectations (Gronross, 1983; Parasuraman, Zeithaml & Berry, 1985)”(REEVES, 1994) Global competitive pressure are causing organizations to find ways to better meet the needs of their customers, to reduce costs, and to increase productivity. Improvement of quality has developed us a focal point in meeting these objectives. Continuous improvement has become a necessary and integral part of the business strategy of organizations. Historically, quality control in the manufacturing and service industries has consisted of inspection of the product or service relative to a set of requirements (specifications). In manufacturing, this function is carried out by the quality control (QC) department. In service industries, the counterpart of the QC department is often called the audit department. Once the product is inspected, it is sorted into batches of good or bad, and the bad product is reworked or scrapped. There are several well-known inadequacies in this approach to improvement of quality, among them: - Issues related to quality are not addressed until it is too late; the product or service is already completed. - Quality is obtained at high cost and with loss of productivity. XI- A“fire fighting”approach to problem solving is adopted, which results in short-term solutions to immediate problems at the expense of long-term improvement. A change in the approach to improve quality is needed. The theory needed for this change is provided by Deming and is known as the“quality and productivity chain reaction.”This theory states that if an organization focuses on the improvement of quality, reduced costs and higher productivity will follow. The organization will then increase market hare through the better quality and lower cost. (MOEN, 1991) At this point, Total Quality Management ( TQM ) rose. TQM is a management philosophy that builds customer driven learning or organizations dedicated to total customer satisfaction with continuous improvement in the effectiveness and the efficiency of the organization and its processes rose. The benefits derived from effective implementation of total quality control which is the early phase of TQM and continuous process improvement have been considered the equivalent of an“industrial revolution”. Until recent years, most traditional productivity and quality improvement programs have been characterized by a product and inspection orientation and have ignored employee contributions. Productivity improvement was assumed to involve high capital expenditures. Instead of these beliefs, TQM inserted new philosophy, that can be summarized as follows: - TQM' s philosophy is a frame for cultural change, - TQM provides a new vision for management leadership, - TQM places the customer as the principle pivot around which company activities rotate, - TQM emphasizes“continuous improvement”of the processes by using appropriate techniques, - TQM seeks employee involvement and empowerment, - TQM de-emphasizes numerical quotas, unfounded numerical goals, and employee performance evaluation, - TQM replaces an antagonistic relationship with cooperation and partnership. The requirements for improvement of quality are a common purpose and knowledge of concepts and methods so that change results in improvement. The overriding goal is continuous improvement in every activity. Getting better and better is more important than whether the current results are good or bad. Quality will be improved through understanding current and future needs of the customer, designing the product to meet those needs, and designing the process that results in the product. The better the knowledge of these processes, the more likely planned changes are to result in improvement. xnThe key factor for success in improvement of quality is learning. It is through learning that improvements in products and services are made. Learning is enhanced by fostering teamwork. Team activities should be centered around the satisfaction of internal and external customers. Management must provide training for teams in the methods of planned experimentation to increase knowledge for improvement of quality. Continuous communication and teamwork between customers and suppliers and between managers and workers will be necessary to identify opportunities for improvement. The advantages of implementing a TQM system are both qualitative and quantitative. The overall benefit is that the company becomes proactive rather than reactive to design and production problems. Financially, the return on investment will materialize through greater sales because there are better product designs and product offerings. These improvements can then be positioned as competitive advantages in the marketplace. There are some other advantages of TQM which can be summarized as: - A change in emphasis from detection to prevention reduces the daily crambling to get products shipped. - Identification of special causes of variation by the help of Statistical Process Control (SPC) and problem solving teams makes shop-floor and design-table problems solves and eliminated from future products. - Lower costs, higher productivity and less rework are reached long before the first parts are manufactured. - Employee moral is improved. -Preventive measures identified or new requirements established by monitoring the effects of process changes before substantial rework is inadvertently generated during the manufacturing process. As it is mentioned above, SPC is one of the most effective tools of TQM. It is the application of statistical principles to reduce defects. It is used by first-line supervisors and their employees. Emphasis is on continuous process monitoring; the assumption is that a process under control will yield acceptable products. The operator establishes the average value and range of deviations from the mean in a process and plots those values in the form of X-bar and R charts. Precontrol limits are set and sample measurements are taken from products being produced. The operator then monitors the outcome of each plot or group of plots to determine ifa trend is developing or if the process is out of control. If it is out of control, the process is stopped, the cause determined, and a solution is implemented. xniFor any process, indicators of the performance of the process can be identified and measured. These indicators will be called quality characteristics. For manufacturing processes, measures such as length, width, viscosity, color, temperature, line speed, number of accidents, and percent rejected materials are examples. Number of errors in billing, number of incorrect transactions in a bank, checkout time in a grocery store, frequency of a program restarts in data processing, and actual expenditures are examples of quality characteristics for service processes. Statistical Process Control is the application of statistical methods to the measurement and analysis of variation in any process. Statistical techniques can make an important contribution to achieving quality objectives. (JURAN, 1993) A statistical control chart is a graphical comparison of process performance data to computed“statistical control limits,”drawn as limit lines on the chart. The process performance data usually consist of groups of measurements (“rational groups”) that come from the regular sequence of production while preserving the order of the data. A prime objective of control chart is detecting special (or assignable) causes of variation in process by analyzing data from both the past and the future. A fundamental concept necessary to the study and improvement of processes introduced by Shewhart (1931) is that variation in the outcome of a process is due to two types of causes: Common causes: Causes that are inherent in the process over time, affect everyone working in the process, and affect all outcomes of the process. Special causes: Causes that are not present in the process all the time or do not affect everyone, but arise because of specific circumstances. Ideally, only common causes should be present in a process because these represent a stable and predictable process which leads to minimum variation. A process that is operating without special causes of variation is said to be“in state of statistical control”. The control chart for such a process has all of the data points within the statistical control limits. The objective of a control chart is not to achieve a state of statistical control as an end in itself but to reduce variation. The control chart distinguishes between common an special causes of variation through its choice of control limits. These are calculated using the laws of probability in such a way that highly improbable causes of variation are presumed to be due not to random or common causes but special causes. When the variation exceeds the statistical control limits, it is a signal that special causes have entered the process and the process should be investigated to identify these causes of excessive variation. SPC is not a prerequisite to total quality control, and SPC alone will not yield a high quality product. Total quality control is much more than the application of statistics in quality problem resolution. A successful quality program involves a three-pronged approach including people, product and process. xiv
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