This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Previous studies reported mixed and ambiguous results of the relationship between TQM practices and performances. This study investigated impacts of TQM practices on various performance measures as well as the reasons and the barriers of the TQM practices of firms in Turkey. We used a cross-sectional survey methodology in this study, and the unit of the sample was at the plant level.
Economics Lean Six Sigma Six Sigma is a quality improvement methodology focused on reducing product or service failure rates to a level of perfection.
Structured, data driven approaches are used to eliminate the number of defects across all business areas, such as management, supply chain, design, manufacturing, and customer satisfaction.
The overall goal is to produce better products and services more efficiently and effectively, while reducing costs. The DMAIC process will assist in defining the problem and scope of the project and ensure that these objectives are accounted for throughout the study.
The concept of Lean centers on the continuous elimination of waste in processes, thereby increasing customer satisfaction while reducing the total costs required to produce the same goods or services.
Common qualitative forecasting methods include expert opinion, sales force polling, the Delphi Method, and customer surveys. Quantitative Forecasting — The historical pattern of the data, i.
Inventory Theory — Scientific inventory management is used to assist companies to determine how much of a product should be ordered, or produced, and when the order should be placed so the total inventory costs are minimized.
Aggregate Production Planning — Consists of efforts to plan a desired output over a longer range by adjusting the production rate, employment, inventory, and other controllable variables. Common pure strategies include varying workforce size to fulfill demand by employment only, to maintain a stable workforce but permit overtime, maintain a stable workforce but carry inventory, implement a backorder strategy, or implement a subcontracting strategy.
Material Requirements Planning MRP — Uses the Master Production Schedule MPS to create schedules that identify parts and subcomponents needed to produce an end product, the quantity of the parts and subcomponents needed, and the dates when the materials need to be ordered. Just-In-Time JIT — A pull system with the goal of reducing the work-in-process to a minimum by only moving items when requested by a higher level in the production process.
Production Planning and Scheduling — Project management is a strategic component that involves planning, organizing, staffing, controlling, and monitoring a project in an efficient and effective manner, thus relating the project results to a business objective.
Job Sequencing and Operations Scheduling — Job sequencing focuses on determining the schedule for machine process jobs such that a specific measure of performance, e.
Assembly Line Balancing ALB analyzes assembly operations such that workstations are assigned in an order to achieve equal balance between stations and increase the overall efficiency and effectiveness of the assembly line.
Markov Chain Analysis — A descriptive technique that provides probabilistic information about a decision situation. Analyzes systems that exhibit probabilistic movement from one state, or condition, to another over time. Queueing Theory — A descriptive modeling technique that describes a solution to allow for analysis of concepts such as the expected number of entities, e.
Optimization Linear Programming — An optimization problem for which the goal is to maximize, or minimize, a linear objective function with respect to a set of linear constraints. Linear programming is used throughout several industries typically with the primary goal of maximizing a profit function or minimizing a cost function.
Common linear programming applications include work-scheduling, budgeting, financial planning, transportation, transshipment, and network models. Integer Programming — A linear program for which some or all of the variables are required to be non-negative integers. Common integer programming applications include investment decision making, facility location, and machine scheduling problems.
Types of nonlinear programming include quadratic, convex, non-convex, geometric, and fractional programming. Multiple Criteria Decision Making — An optimization problem for which several conflicting criteria are simultaneously optimized.
An example of multiple criteria decision making is goal programming, which chooses one of the multiple criteria as the primary criterion and use it as the objective function to be optimized.
The remaining criteria are assigned acceptable values and treated as constraints. The criteria are treated as targets with the goal of producing a solution as close as possible to the targets based on priorities.
Heuristic algorithms are used in many applications, but one common area of application are network analysis models. Data Analysis and Management Data Collection — Develop comprehensive data collection plans to assure that unbiased and relevant data is collected to answer the questions being asked and stay within scope.
Data Analysis — Apply advanced statistical tools, such as hypothesis testing, statistical process control, process capability analysis, analysis of variance, regression analysis, root cause analysis, and design of experiment to appropriately draw conclusions about the available data.
Big Data Mining — Use advanced tools, such as pivot tables, to stratify and analyze large amount of data in an efficient and effective manner.
Very useful in determining what data and information is available and what data may need to be collected in order to answer a question or finish a project. Data Management — Develop user friendly tools that will allow for easy manipulation of data and allow for efficient and effective analysis.
With a few clicks, easily run several courses of action to quantify key parameters, such as cost and performance. Data Reports — Provide thorough reports discussing the project from start-to-finish, including the data collection and analysis processes, as well as all conclusions that resulted.
Will also provide concise executive summaries for upper management personnel to highlight the main findings from the study.10/Dimerco dedicates to Academia-Industry Collaboration with Takming University of Science and Technology in Vietnam. significant relationship between supply chain management strategy and financial performance.
4th Hypothesis: There is a significant relationship between logistics performance and marketing performance. 5th Hypothesis: There is a significant relationship between logistics. By creating a set of linkages between the work that is being performed and the financial outcomes of the firm, the organization’s supply chain function can gain organizational visibility and demonstrate the impact of supply chain decisions and resource utilization on the firm’s financial performance.
between financial and non-financial performance measures. This stream of research supported the idea that non- financial performance measures can be indicators for current or . Recent research on total quality management (TQM) has examined the relationships between the practices of quality management and various levels of organizational performance.
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