Application of Fuzzy Multi-Criteria Decision Making Methods on Six Sigma Projects Selection

Abstract. Six sigma method widely applied in production and service businesses is known as a project-oriented method. In six sigma method, selection of the prior project among others can be considered as a multi -criteria decision making problem. The conducted literature review has revealed that there is a large number of methods to select six sigma projects. It is more appropriate to use fuzzy multi-criteria decision making methods in project selection since evaluation criteria of six sigma projects include uncertainties. The aim of this study is to select the most appropriate project as a result of evaluating the projects by Fuzzy VIKOR, Fuzzy TOPSIS and Fuzzy COPRAS as methods of fuzzy multicriteria decision-making and integrating the ranking scores obtained from each method by Copeland method. The proposed method has been implemented in a large scale production company, operating in Aydın ASTİM Organized Industrial Zone.Keywords. Six Sigma Projects, Fuzzy VIKOR, Fuzzy TOPSIS, Fuzzy COPRAS, Fuzzy AHP, Copeland Method.JEL. M11, C44, L20, C02, D70, O22

An Analytical Approach to Lean Six Sigma Deployment Strategies: Project Identification and Prioritization

abstract: The ever-changing economic landscape has forced many companies to re-examine their supply chains. Global resourcing and outsourcing of processes has been a strategy many organizations have adopted to reduce cost and to increase their global footprint. This has, however, resulted in increased process complexity and reduced customer satisfaction. In order to meet and exceed customer expectations, many companies are forced to improve quality and on-time delivery, and have looked towards Lean Six Sigma as an approach to enable process improvement. The Lean Six Sigma literature is rich in deployment strategies; however, there is a general lack of a mathematical approach to deploy Lean Six Sigma in a global enterprise. This includes both project identification and prioritization. The research presented here is two-fold. Firstly, a process characterization framework is presented to evaluate processes based on eight characteristics. An unsupervised learning technique, using clustering algorithms, is then utilized to group processes that are Lean Six Sigma conducive. The approach helps Lean Six Sigma deployment champions to identify key areas within the business to focus a Lean Six Sigma deployment. A case study is presented and 33% of the processes were found to be Lean Six Sigma conducive. Secondly, having identified parts of the business that are lean Six Sigma conducive, the next steps are to formulate and prioritize a portfolio of projects. Very often the deployment champion is faced with the decision of selecting a portfolio of Lean Six Sigma projects that meet multiple objectives which could include: maximizing productivity, customer satisfaction or return on investment, while meeting certain budgetary constraints. A multi-period 0-1 knapsack problem is presented that maximizes the expected net savings of the Lean Six Sigma portfolio over the life cycle of the deployment. Finally, a case study is presented that demonstrates the application of the model in a large multinational company. Traditionally, Lean Six Sigma found its roots in manufacturing. The research presented in this dissertation also emphasizes the applicability of the methodology to the non-manufacturing space. Additionally, a comparison is conducted between manufacturing and non-manufacturing processes to highlight the challenges in deploying the methodology in both spaces.Dissertation/ThesisPh.D. Industrial Engineering 201

Fuzzy Process Control And Development Of Some Models For Fuzzy Control Charts

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2006Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2006Bu çalışmada, bulanık kümeler teorisi kullanılarak belirsizlik içeren dilsel verilerin kontrol diyagramlarına yeni yaklaşımlar geliştirilmiştir. Belirsizlik içeren dilsel veriler, bulanık sayılarla ifade edilmiştir. Dilsel veriler için bulanık kontrol diyagramları α-kesim yaklaşımı kullanılarak geliştirilmiş ve bu suretle muayene sıklığı tanımlanmıştır. Bulanık kontrol diyagramlarının oluşturulmasında, bulanık verilerin taşıdığı bilgilerin kaybolmasını önlemek amacıyla “Direkt Bulanık Yaklaşım” geliştirilmiştir. Bulanık verilerin kontrol diyagramındaki normal olmayan davranış testleri için bulanık bir yaklaşım geliştirilmiştir. Önerilen yaklaşımların pratik kullanımlarının yansıtılması açısından gerçek verilere dayalı nümerik örnekler sunulmuştur.In this study, process control charts under linguistic, vague, and uncertain data are developed in the light of the Fuzzy Set Theory. Linguistic or uncertain data are represented by the use of fuzzy numbers. Fuzzy control charts for the linguistic data are proposed and integrated with the α-cut approach of fuzzy sets in order to set the degree of tightness of the inspection. A new approach called direct fuzzy approach to fuzzy control charts is modeled in order to prevent the loss of information of the fuzzy data during the construction of control charts. Finally, fuzzy unnatural pattern analyses are developed to monitor the abnormal patterns of the fuzzy data on the control charts. Numerical examples using the data of a real case are also given to highlight the practical usage of the proposed approaches.DoktoraPh

A FRAMEWORK FOR STRATEGIC PROJECT ANALYSIS AND PRIORITIZATION

Projects that support the long-term strategic intent and alignment are considered strategic projects. Therefore, these projects must consider their alignment with the organization’s current strategy and focus on the risk, organizational capability, resources availability, political influence, and socio-cultural factors. Quantitative and qualitative methods prioritize the projects; however, they are usually suitable for specific industries. Although prioritization models are used in the private sector, the same in the public sector is not widely seen in the literature. The lack of models in the public sector has happened because of the projects’ social implications, the value perception of different projects in the public sector, and potentially differing value perceptions attached to the types of projects in different decision-making environments in the public sector. The thesis proposes a generic framework to develop a priority list of the available basket of projects and decide on projects for the next undertaking. The focus of the thesis is on public projects. The analysis in the framework considers the critical factors for prioritization obtained from the literature clustered through the agglomerative text clustering technique. In the proposed framework, 13 critical clusters are identified and weighted using the Criteria Importance Through Intercriteria Correlation (CRITIC) method to develop their ranking using the Technique for Order of Preference Similarity Ideal Solution (TOPSIS) method. In addition, the proposed framework uses vector weighting to prioritize projects across industries. The applicability of the framework is demonstrated through Qatar’s real estate and transportation projects. The outcome obtained from the framework is compared with those obtained through the experts using the System Usability Scale (SUS). The comparison shows that the framework provides good predictability of the projects for implementation

Solution Space Exploration in Model-Based Realization of Engineered Systems

With growing interest in the model-based realization of engineered systems there is a need for developing methods to explore the solution space that is defined by models that approximate reality and are typically incomplete, inaccurate with different fidelities. These characteristics of model-based engineered systems manifest as uncertainties in the projected outcomes and it requires good understanding, insight and analysis of the designs/solutions in order to support the designer in the process of decision making. Therefore, a significant and desirable step in any model-based realization of engineered systems is to explore the solution space and find desired and robust designs insensitive to variations of different sources. In this thesis a method is proposed to conduct solution space exploration in model-based realization of engineered systems. The construct that is adapted to develop the models is the compromise Decision Support Problem (cDSP). The solutions that form the solution space in the compromise DSP comprises the space defined by the constraints and variable bounds, and the achieved and aspiration space defined by the goals. The main components of the proposed method are: exploring design goals through goal ordering and weight sensitivity analysis, exploring constraints through constraint sensitivity analysis, and incorporating feasibility robustness. The proposed method in this thesis is illustrated in three different design examples namely a small power plant, shell and tube heat exchanger and continuous casting of steel. The emphasis is on the method rather than the results per se. To generalize the method, the post solution analysis template is proposed to facilitate executability and reusability of the solution space exploration method in a computer