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A literature review on six sigma
In this study, the roots, historical development, theoretical background, and future expectations of six sigma quality improvement approach, which emerged in manufacturing industries in the mid 1980s, are analyzed within the framework of an academic literature review. In this context, firstly the historical developments of quality phenomenon in the Western World, Japan, and Turkey are explored, and the theoretical basis of this quality system is identified. Then, the academic journals covered by Science Citation Index (SCI) Expanded are searched without time limits with keyword ?six sigma?. Almost all of the articles in the resulting set are examined in full-text; and a comparative statistical analysis is conducted. This analysis is based upon factors that are derived directly from the contents of the articles. Analysis results are used in order to determine the current situation, up-to-date trends, and historical transformations in the literature, therefore the implementations of six sigma. The results are discussed in detail and ideas about the future implementations of six sigma are given.The literature study shows that although no consensus is built up on either the definition or the implementation of six sigma, it is believed that it will maintain its importance in the following years.
Advanced analysis system for optimized changeover operations
In this study changeover operations are discussed in scope of Lean Manufacturing and Shigeo Shingo?s approach called SMED (Single Minute Exchange of Dies) is explained. SMED approach is analyzed in terms of sustainability and a new analysis system is introduced to develop optimal changeover procedure which tries to provide a sustainable changeover process. On this way the new analysis system is handled under two main headlines; Macro analysis (using conventional SMED approach) and Micro analysis (using MTM / Method Measurement Time Systems). Macro and micro analysis results are documented as changeover procedures which provide the manual for operators to perform the best organized changeover operation.Keywords: SMED (Single Minute Exchange of Dies), Lean Manufacturing, sustainability, changeover, MTM (Method Time Measurement), Time Study, Change
Capacity planning in a textile company
This thesis provides the opportunity of launching the capacity planning system in a company in the textile sector. The objective of this project is handling the demand fluctuations by utilizing regular time working capacity and subcontractor capacity for each product group in a predetermined planning period and giving the customer realistic due dates. To fulfill this target, it is essential to keep the company?s and subcontractor?s production costs at the minimum while meeting the due dates at optimum.In order to achieve these goals a hybrid approach involving a two phased solution methodology is carried out. First an allocation problem is solved using mathematical programming following the assignment of jobs to the facilities under given capacity constraints. Afterwards, a detailed simulation model of the production floor is run to determine in which order the jobs will be processed on these facilities. The output of the mathematical programming model is used as an input for the simulation model. The use of analytical modeling and simulation together as a hybrid approach leads to a mathematically optimal and a realistically feasible solution.
Product reliability
This study presents product reliability on component basis and investigates the possible effects on warranty which constitutes a non-technical issue. Product reliability is a key factor which is used in considering the warranty period. It plays a significant role that a mistake in warranty forecasting costs a lot for companies.The objective is to empirically examine the nature of general reliability of manufactured goods and define a statement about them, based on findings of practicing in an electronics company. In this regard reliability will be stated from the actual manufacturing point of view. A case study was conducted as an application to consider how product reliability results in manufacturing industry. LCD TVs were undertaken to examine. To test reliability, a parametric Weibull model was exploited and hazard rates of products were estimated with linear regression method. For this research, the lifetime data obtained by service departments, censored both left and right, were used in MINITAB14 to produce the reliability results.The results of the analysis build up the basis for evaluating the performance of LCDs in means of service. By the help of it, upcoming failures were forecasted and defined when and how many of them could occur in say six months, a year or two years. The time at which a particular percentage of the production will have failed can be determined
Solving mixed-model assembly line sequencing problem using adaptive genetic algorithms
The focus of this M.Sc study is to introduce adaptive Genetic Algorithm (GA) based approaches for single- and multi-objective mixed-model assembly line sequencing problems (MMALSP), which deal with the determination of production launching orders so that the variations in part consumption rates (VPC) are minimized. In addition to this objective, minimization of total utility work (UW) and cost for sequence-dependent setups (SC) are also considered in multi-objective version of the MMALSP.In order to solve single-objective MMALSPs, an adaptive GA based approach which incorporates adaptive parameter control techniques into a pure GA is proposed. The proposed approach, integrates an adaptive elitist strategy and a scheme for varying probability of mutation according to the feedback taken from the algorithm. Using this approach, the MMALSP is solved under the objective of minimizing VPC in a four level assembly environment, i.e. product, subassembly, component and raw material.Later, by modifying the adaptive parameter control techniques and integrating them into a Pareto Stratum ? Niche Cubicle GA, a multi-objective MMALSP with three objective functions (i.e., minimization of VPC, UW and SC) is solved. Finally, to evaluate the performance of the proposed approach, various sets of experiments have been carried out.
Araç rotalama problemi tipleri için kesin ve sezgisel algoritmalar
As the world is globalizing, distribution of goods and services becomes an inevitable part of both trade and daily life. Distribution of goods and services from a supply point to various demand points is called logistics. A complete logistics system includes transporting materials from a number of suppliers to the factory plant for manufacturing, transporting the products to warehouses and finally distributing them to the customers. Both the supply and distribution procedures require effective transportation planning. Good transportation planning can save a company a considerable amount of its total distribution costs.Vehicle Routing Problem (VRP) basically considers transportation planning and has received a lot of attention in operations research literature due to its commercial value. VRP consists of designing m vehicle routes to minimize total cost, each starting and ending at the depot such that each customer is visited exactly once. Since VRP was first introduced in literature, many variations have appeared by including additional assumptions into the problem.In this dissertation, three of the variants of VRP, which are faced quite often in real life distribution problems, are considered. These are heterogeneous VRP (HVRP), split delivery VRP (SDVRP) and VRP with time windows (VRPTW). A novel Threshold Algorithm is developed for HVRP, SDVRP and small scale VRPTW. For large scale VRPTW, a SetCovering Algorithm is developed.In order to see the efficiency and performance of these algorithms, they are tested on the literature benchmark problems. The results of the computational experiments indicate that the proposed methodologies are useful tools especially for large scale real life problems where fast decision making is of crucial importance. In addition to performance tests, the proposed methodologies are employed to solve the real life fresh goods distribution problem of a retail chain store. The results achieved are presented to the firm and new distribution strategies are offered.
An integrated multi-criteria decision making methodology for risky investment projects evaluation
The aim of this research is to propose a novel methodology for risky investment projects evaluation. The proposed methodology consists of three main stages. The first stage of the methodology includes opportunity and pre-feasibility studies. The aim of this stage is to give prominence to project ideas which have the highest chance of attaining the goals planned by entrepreneurs and investors. Therefore, in the first stage, the investment projects are classified by using a multi-criteria sorting (MCS) method which does not require a training sample, and takes into account the inherent risk and uncertainty associated with the values of evaluation criteria. This MCS method named as PROMSORT was proposed for financial classification problems. In the scope of this dissertation, this method has been adapted to the investment project evaluation and selection problems.After assigning of the project alternatives to the groups, the second stage of the proposed methodology begins. In this stage, a new net present value (NPV) formulation that eliminates the weakness of using the traditional formulation of NPV has been developed. In uncertain and risky environments, the risky project parameters are determined by probability distributions by using simulation models. For that reason, in the second stage, a computer simulation model for new NPV formulation has been developed by using computer simulation software. Also, the second simulation model has been developed in order to calculate the expected cash flows for each project in each period.The budgets of the enterprises are generally not enough to implement all of the investment proposals which have high expected utility level at the same time. In these cases, the enterprises prefer to implement the investment project proposals at the number allowed by the size of their budgets. Besides the lack of budget, the other reasons of this complexity may be some technical limitations such as earliest and latest start dates and precedence relations.However, in today?s high competitive environments, enterprises have to act well-planned. The first step of acting well-planned is to determine a planning horizon and to predict how much budget to allocate for carrying out investment projects each period over that planning horizon. In this new case, the main objective of enterprises is to maximize the expected utility of all investment projects which are carried out over the planning horizon. In the third stage of the proposed methodology, this type of problem is called as optimal project selection and scheduling problem. The last original contribution of this dissertation is to construct multi-objective mathematical models such as multi-objective linear programming model and fuzzy multi-objective linear programming models in order to solve this problem.
Facility layout optimization using simulation in an automative company
The aim of this study is to transform an assembly line in an automotive company on which only one type of a car can be operated, into a flexible assembly line on which different types of cars can be operated at the same time.In this company, two different car models will start being produced on the same assembly line instead of one. Therefore, some changes in the system are needed to be made. In the first stage of this thesis, current production system, facility layout and transportation activities are examined and problems of the system are determined. In the system, there is not an effective material handling and stock control system and parts are being damaged and delays are occurring during the transportation. In order to solve these problems and make production system more flexible, some improvements are proposed. A pull system which controls production between departments and quantity of work in progress is developed. Facility layout for new coming models is also designed and in order to perform transportation operations in more effective way with minimum cost, AGV (automatic guided vehicle) system is suggested instead of forklifts.In this thesis, also a simulation study was developed to see at what degree the improvements increase the system performance and to find the optimum value of decision variables by using ARENA 10.0.
Implementation of Kaizen Blitz approach in an electronics firm
In this thesis implementation of the Kaizen Blitz approach, known as one of the principles of the total quality control applications and lean manufacturing, in an electronic company is presented. First, problems faced by the company before the execution of this approach are defined, and then implementation steps and expected improvements that will result from carrying out the Kaizen Blitz approach are given in detail.
A hbyrid genetic algorithm for mixed-model assembly line balancing problem with parallel workstation assignment
In this thesis, we deal with the mixed-model assembly line balancing problem (MMALBP) of type-1, which consists of finding a number of stations for a predetemined cycle time as well as a line balance such that a capacity- or even cost-oriented objective is optimized. Various exact and approximation approaches have been developed to deal with MMALBP of type-1. Due to the NP-hard structure of the problem none of the optimum seeking methods have been proven to be practical to solve large scale problems. Moreover, approximation methods may lack the capability of exploring the solution space effectively. Over the last years, hybrid meta heuristics which combine the various algorithmic ideas of meta-heuristics concerning overcome these shortages have been reported.In this thesis, we propose an effective hybrid genetic algorithm, which is able to address some particular features such as parallel workstations and zoning constraints of the assembly process for MMALBP of type-1. For the hybridization of genetic algorithm three well known heuristics, Kilbridge and Wester Heuristic, Phase-I of Moodie and Young Method, and Ranked Positional Weight Tecnique are used. The original versions of them only address the simple assembly line balancing problem, where one single model is assembled, no parallel workstations are allowed and zoning constraints are not considerd. Therefore, we modified Kilbridge and Wester and Phase-I of Moodie and Young Methods for applying these heuristics to MMALBP. Comparative experiments are carried out to evaluate the performances of modified versions of the these heuristics, simulated annealing, pure genetic algorithm, ANTBAL and the proposed procudure on a benchmark data set including 20 MMALBPs of type 1. The proposed hybrid genetic algorithm outperformed the other heuristics and pure genetic algorithm. Although the proposed hybrid genetic algorithm explored the same performance with ANTBAL, it requires less computational effort than ANTBAL.