International Journal of Advanced Manufacturing Technology
With a view to monitoring and controlling manufacturing processes in industries control charts ar... more With a view to monitoring and controlling manufacturing processes in industries control charts are widely used to a great extent and needed to be designed economically to achieve minimum quality costs. Many authors have studied economic design of X-bar control chart after Duncan (1956) first proposed the economic model of X-bar control chart for single assignable cause. But in practice multiple assignable causes are more logical and realistic. Moreover the economic design does not consider statistical properties like bound on type- I, type- II error and average time to signal (ATS). This paper focuses on evaluating the performance of genetic algorithm (GA) in pure economic and economic statistical design of X-bar control chart for multiple assignable causes. The performances of GA is demonstrated by comparing its result with previously proposed grid search technique for a numerical example. Duncan model of multiple assignable causes with taking into account statistical properties is adopted to formulate objective function as cost minimization and the computation is achieved by approximation through a numerical method named Simpson’s 1/3 rule. Comparison distinctly shows the superiority of GA over grid search results for economic statistical design.
International Journal of Productivity and Quality Management
Control charts are very popular for monitoring production processes and designed economically to ... more Control charts are very popular for monitoring production processes and designed economically to achieve minimum quality costs. This paper focuses on evaluating the performance of genetic algorithm (GA) and simulated annealing algorithm (SAA) in economical design of X-bar control chart.The performances of GA and SAA is demonstrated through a numerical example and the results were compared with Montgomery (1982). To outperform Montgomery’s approach the paper dealt with the same example and demonstrate its utility. Duncan model of single assignable cause without taking into account process improvement and statistical properties is adopted to formulate the cost minimizing equation and the computation is achieved through Simpson’s one-third approximation rule. A comparison between the performance of GA and SAA is also exhibited in this paper.
International Journal of Productivity and Performance Management
Managers encounter many decisions that require the simultaneous use of different types of data in... more Managers encounter many decisions that require the simultaneous use of different types of data in their decision-making process. A critical decision area for managers is the performance evaluation of personnel, whether individually or as a member of a team. Performance evaluation is critically essential for the effective management of the human resource of an organization and evaluation of staff that help develop individuals, improve organizational performance, and feed into business planning. Performance evaluations require and often involve disparate types of information that are vague, incomplete, objective, and subjective. This paper proposes a performance evaluation system of employees considering various performance evaluation criteria using fuzzy logic. The main task in the proposed approach involves determining the performance indices of employees considering their respective performance in various qualitative and quantitative evaluation criteria and then selecting the best employee who holds highest performance index comparing all the indices. Fuzzy control is used to determine the overall performance index by combining results of the performance in selected criteria and provided it in numerical values which will undoubtedly ensure convenience of the concerned human resource personnel during performance rating calculation. MATLAB Fuzzy Logic Tool Box is used to develop the fuzzy model.
In today’s competitive business, supplier selection problem plays a significant role as a strateg... more In today’s competitive business, supplier selection problem plays a significant role as a strategic feature in company's success. Supplier selection problem usually is very complex and unstructured, because variety of uncontrollable and unpredictable factors affects the evaluation and decision-making process at different levels. Various decision making approaches have been proposed to tackle the problem as part of a general tendering process, particularly those of multi-criteria analysis which use both quantitative and qualitative data. The aim of this paper is to integrate fuzzy Delphi method with fuzzy analytic hierarchy process (AHP) and fuzzy TOPSIS based approach to select the best supplier providing the highest satisfaction for the criteria determined. Fuzzy Delphi method is used to identify the most important and significant criteria then fuzzy AHP is used to obtain the relative importance of the evaluation criteria and finally fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is used to rank the suppliers with a view to select the best one from them. In order to demonstrate the applicability of proposed approach an illustrative example is presented and the result is analyzed at the end of this paper.
In today’s competitive business, supplier selection problem plays a significant role as a strateg... more In today’s competitive business, supplier selection problem plays a significant role as a strategic feature in company's success. Supplier selection problem usually is very complex and unstructured, because variety of uncontrollable and unpredictable factors affects the evaluation and decision-making process at different levels. Various decision making approaches have been proposed to tackle the problem as part of a general tendering process, particularly those of multi-criteria analysis which use both quantitative and qualitative data. The aim of this paper is to integrate fuzzy analytic hierarchy process (AHP) and fuzzy TOPSIS based approach to select the best supplier providing the highest satisfaction for the criteria selected. Fuzzy AHP is used to obtain the relative importance of the evaluation criteria and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is used to rank the suppliers with a view to select the best one from them. In order to demonstrate the applicability of proposed approach an illustrative example is presented and the result is analyzed at the end of this paper.
SAE International Journal of Materials and Manufacturing
Predicting the main cutting force during turning is of great importance as it helps in setting th... more Predicting the main cutting force during turning is of great importance as it helps in setting the appropriate cutting parameters before machining starts. Again, optimization of cutting parameters is one of the most important elements in any process planning of metal parts as economy of machining operation plays a key role in gaining competitive advantage. This paper presents an experimental study of main cutting force in turning of AISI 1040 steel and developing a model of the main cutting force during turning using Response surface Methodology (RSM) as well as optimization of machining parameters using Genetic Algorithm (GA). The second order empirical model of the main cutting force in terms of machining parameters are developed based on experimental results. The experimentation is carried out considering three machining parameters: cutting speed, feed rate and depth of cut as independent variables and the main cutting force as the response variable. The formulated model is validated against new set of experimental values using Mean Absolute Percent Error (MAPE) method. The Genetic Algorithm approach is also used to optimize the cutting parameters to keep the main cutting force to a minimum.
International Journal of Advanced Manufacturing Technology
With a view to monitoring and controlling manufacturing processes in industries control charts ar... more With a view to monitoring and controlling manufacturing processes in industries control charts are widely used to a great extent and needed to be designed economically to achieve minimum quality costs. Many authors have studied economic design of X-bar control chart after Duncan (1956) first proposed the economic model of X-bar control chart for single assignable cause. But in practice multiple assignable causes are more logical and realistic. Moreover the economic design does not consider statistical properties like bound on type- I, type- II error and average time to signal (ATS). This paper focuses on evaluating the performance of genetic algorithm (GA) in pure economic and economic statistical design of X-bar control chart for multiple assignable causes. The performances of GA is demonstrated by comparing its result with previously proposed grid search technique for a numerical example. Duncan model of multiple assignable causes with taking into account statistical properties is adopted to formulate objective function as cost minimization and the computation is achieved by approximation through a numerical method named Simpson’s 1/3 rule. Comparison distinctly shows the superiority of GA over grid search results for economic statistical design.
International Journal of Productivity and Quality Management
Control charts are very popular for monitoring production processes and designed economically to ... more Control charts are very popular for monitoring production processes and designed economically to achieve minimum quality costs. This paper focuses on evaluating the performance of genetic algorithm (GA) and simulated annealing algorithm (SAA) in economical design of X-bar control chart.The performances of GA and SAA is demonstrated through a numerical example and the results were compared with Montgomery (1982). To outperform Montgomery’s approach the paper dealt with the same example and demonstrate its utility. Duncan model of single assignable cause without taking into account process improvement and statistical properties is adopted to formulate the cost minimizing equation and the computation is achieved through Simpson’s one-third approximation rule. A comparison between the performance of GA and SAA is also exhibited in this paper.
International Journal of Productivity and Performance Management
Managers encounter many decisions that require the simultaneous use of different types of data in... more Managers encounter many decisions that require the simultaneous use of different types of data in their decision-making process. A critical decision area for managers is the performance evaluation of personnel, whether individually or as a member of a team. Performance evaluation is critically essential for the effective management of the human resource of an organization and evaluation of staff that help develop individuals, improve organizational performance, and feed into business planning. Performance evaluations require and often involve disparate types of information that are vague, incomplete, objective, and subjective. This paper proposes a performance evaluation system of employees considering various performance evaluation criteria using fuzzy logic. The main task in the proposed approach involves determining the performance indices of employees considering their respective performance in various qualitative and quantitative evaluation criteria and then selecting the best employee who holds highest performance index comparing all the indices. Fuzzy control is used to determine the overall performance index by combining results of the performance in selected criteria and provided it in numerical values which will undoubtedly ensure convenience of the concerned human resource personnel during performance rating calculation. MATLAB Fuzzy Logic Tool Box is used to develop the fuzzy model.
In today’s competitive business, supplier selection problem plays a significant role as a strateg... more In today’s competitive business, supplier selection problem plays a significant role as a strategic feature in company's success. Supplier selection problem usually is very complex and unstructured, because variety of uncontrollable and unpredictable factors affects the evaluation and decision-making process at different levels. Various decision making approaches have been proposed to tackle the problem as part of a general tendering process, particularly those of multi-criteria analysis which use both quantitative and qualitative data. The aim of this paper is to integrate fuzzy Delphi method with fuzzy analytic hierarchy process (AHP) and fuzzy TOPSIS based approach to select the best supplier providing the highest satisfaction for the criteria determined. Fuzzy Delphi method is used to identify the most important and significant criteria then fuzzy AHP is used to obtain the relative importance of the evaluation criteria and finally fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is used to rank the suppliers with a view to select the best one from them. In order to demonstrate the applicability of proposed approach an illustrative example is presented and the result is analyzed at the end of this paper.
In today’s competitive business, supplier selection problem plays a significant role as a strateg... more In today’s competitive business, supplier selection problem plays a significant role as a strategic feature in company's success. Supplier selection problem usually is very complex and unstructured, because variety of uncontrollable and unpredictable factors affects the evaluation and decision-making process at different levels. Various decision making approaches have been proposed to tackle the problem as part of a general tendering process, particularly those of multi-criteria analysis which use both quantitative and qualitative data. The aim of this paper is to integrate fuzzy analytic hierarchy process (AHP) and fuzzy TOPSIS based approach to select the best supplier providing the highest satisfaction for the criteria selected. Fuzzy AHP is used to obtain the relative importance of the evaluation criteria and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) is used to rank the suppliers with a view to select the best one from them. In order to demonstrate the applicability of proposed approach an illustrative example is presented and the result is analyzed at the end of this paper.
SAE International Journal of Materials and Manufacturing
Predicting the main cutting force during turning is of great importance as it helps in setting th... more Predicting the main cutting force during turning is of great importance as it helps in setting the appropriate cutting parameters before machining starts. Again, optimization of cutting parameters is one of the most important elements in any process planning of metal parts as economy of machining operation plays a key role in gaining competitive advantage. This paper presents an experimental study of main cutting force in turning of AISI 1040 steel and developing a model of the main cutting force during turning using Response surface Methodology (RSM) as well as optimization of machining parameters using Genetic Algorithm (GA). The second order empirical model of the main cutting force in terms of machining parameters are developed based on experimental results. The experimentation is carried out considering three machining parameters: cutting speed, feed rate and depth of cut as independent variables and the main cutting force as the response variable. The formulated model is validated against new set of experimental values using Mean Absolute Percent Error (MAPE) method. The Genetic Algorithm approach is also used to optimize the cutting parameters to keep the main cutting force to a minimum.
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Papers by Imtiaz Ahmed