Table 2 - uploaded by Thenarasu Mohanavelu
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... next step is to find out a pair-wise comparison matrix where data's are collected from experts or decision-makers corresponding to the hierarchic structure for the pair wise comparison of alternatives on a qualitative scale. The comparisons are made for each criterion and converted into quantitative numbers as per Table 2 suggested by Saaty (2008). The pair wise comparisons of various criteria generated are organised into a square matrix. ...
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... Snyman and Bekker (2019) applied various dispatching rules for a dynamic JSSP. A simulation model of an auto ancillary unit to prioritize jobs, using an Analytic Hierarchy Process (AHP) based priority rules in a press shop was developed and designed (Mohanavelu et al. 2017). Thenarasu et al. (2019), also proposed using an Arena simulation model to evaluate performance measures, integrating PDRs and Multi-Criteria Decision-Making (MCDM) with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach (Thenarasu et al. 2020). ...
Job shop scheduling problem (JSSP) has remained a challenge both for the practitioners and the researchers. A JSSP consists of multiple number of machines (m) and jobs (n). As the number of jobs increases, the complexity of the problem increases exponentially and it becomes difficult to schedule manually. Many papers in the literature discuss heuristic and metaheuristic solutions to solve Job shop scheduling problems. But there is no ease of use for practitioners who rely on their experience to schedule jobs in ad hoc sessions resulting in inefficient allocation of jobs and machines. In this paper, a job shop scheduling problem under static and dynamic conditions is solved using heuristic approaches using python programming with an MS Excel user interface. For a supplier of automotive parts with a set of jobs and machines, priority dispatching rules, viz., Shortest Processing Time (SPT), Earliest Due Date (EDD), First-In First-Out (FIFO), Critical Ratio (CR) and Slack Per Remaining Operation (S/RO) are evaluated. The obtained performance metrics such as makespan, and tardiness are compared between the heuristics to select an optimal schedule by the job shop. The user inputs the jobs, machines, start and due dates through the MS Excel interface and obtains faster, practically usable results. This reduces the time taken for job scheduling and helps in making faster productivity-based decisions to maximize resource utilization and the total time to produce the product. Integrating Python at the backend and Excel at the front end will encourage many MSMEs to perform optimized scheduling using heuristics thereby reducing the throughput time. Key words: Job shop scheduling problem, priority dispatching rules, python programming, micro small and medium enterprises. Padmanabhan et al./Decis. Mak. Appl. Manag. Eng. 5 (2) (2022) 201-218 202
... AHP based PDR was proposed by Mohanavelu et al., [31] considering real-time criteria such as production volume, due date, and cycle time to minimize the lead-time of a large-scale press shop. Different PDRs were comparatively evaluated in their study to minimize lead time, waiting time, WIP and improve machine utilization. ...
Flexible job shop scheduling problem (FJSSP) is a critical operational planning step in manufacturing that ensures on-time delivery of goods leading to customer satisfaction. The process of assigning jobs to machines has a larger solution space and consumes a huge amount of time and effort. This research focuses on solving FJSSP using the discrete event simulation (DES) model and integrates it with Composite Dispatching Rules (CDRs) and multi-criteria decision making (MCDMs) based priority rules. Performance evaluation of the flexible job shop is carried out to minimize the Makespan, mean Flow-Time, mean Tardiness, and maximum Tardiness. Best performing CDRs and hybrid MCDM techniques are employed for minimizing the objectives considered in this study. The proposed solution framework integrates Fuzzy Analytic Hierarchy Process (FAHP) for assigning weights to the criteria and MCDM approaches namely technique for order of preference by similarity to ideal solution (TOPSIS), The Evaluation based on Distance from Average Solution (EDAS), Compromise Programming (CP), and Weighted Average Method (WAM) separately to prioritize the jobs. Benchmark problems of different sizes are tested using the best performing CDRs available in the literature and proposed MCDM approaches. The proposed approach is implemented in a real-world large-scale flexible job shop (FJS) that produces auto components handling 114 job variants with 245 operations using 28 machines. The performance analysis indicates that no single rule outperforms all the objective measures considered in this study. The MCDMs based rules perform better compared to CDRs for large-scale problems by considering realistic criteria such as demand, due date, setup time, process time, customer priority, and number of operations. The methodology proposed in this study can be tailored in terms of the criteria used for ranking and production parameters to be executable for any real-time instance.
... The present study fills the gap in literature by conducting the assessment and measurement of the agile success factors using Two-way assessment and analytic hierarchy process (AHP) (Mohanavelu et al., 2017) to determine the maturity of the agile implementation in an enterprise. The measurement of the agile success factors will enable the practitioners to determine the maturity of agile implementation and make improvements based on the measurement result. ...
... Simulation plays an important role in decision making in dynamic environments (Mohanavelu et al., 2017). To demonstrate the feasibility of the proposed system and to evaluate the effectiveness of the existing and proposed systems on performance, we use the simulation approach (Sahin et al., 2017). ...
... An assessment demonstrates based on FAHP and TOPSIS, it is created to assist the mechanical specialists for the execution assessment in a proper environment which is fuzzy where the subjectivity and the inaccuracy are dealt with the etymological values that are ranked by fuzzy numbers (triangular). The strategy empowers choice investigators to make a better total assessment and give a more exact, compelling, and precise decision support tool [10][11]. Sun and Lin (2012) taking into thought innovation acknowledgment variables, site benefit quality, and particular toll factors, explore how shopping websites build up their competitive advantages. ...
Customer Relationship Management (CRM) is a new competitive way or approach for organizations that serve both internal and external customers. Organizations today focus on conquering the customers' minds, by giving them the "WOW FACTOR"-customer satisfaction which makes them delighted. This work explores how CRM can be used to increase the effectiveness of the organizational interface towards customer satisfaction, loyalty, and decrease the customer defection rate. To study this, a manufacturing company has been selected as our objective company. An exponential increase in customer defection rate was identified as the major issue. From a series of surveys conducted along with the company and clients, it was found "Delayed Delivery" was the major reason for the increasing customer defection rate. To decrease customer defection rate, a mathematical model has been developed to rank the orders using Fuzzy Analytical Hierarchy Process (FAHP) which is then used to find weights of the criteria by constructing pair wise comparison matrix and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with four different methods of normalization. The same was implemented in the company and the results were evaluated and analyzed. After implementing the model, it was found that there has been a substantial increase in customer satisfaction rate of 37% compared to the previous month.
... Simulation plays an important role in decision making in dynamic environments (Mohanavelu et al., 2017). To demonstrate the feasibility of the proposed system and to evaluate the effectiveness of the existing and proposed systems on performance, we use the simulation approach (Sahin et al., 2017). ...
There are continuing debates on the effects of enterprise resource planning (ERP) and its combination with lean on manufacturing performance. It is suggested to integrate lean production principles into ERP systems; however, research exploring this area in the literature is limited, especially quantitative studies. This study fills the knowledge gap by quantitatively investigating the correlation between ERP-based lean systems and performance outcomes, using a system dynamics approach. We model a manufacturing system, focusing on the effects of ERP and lean inputs on customers' order fulfilment. Different scenarios of ERP systems supporting lean practices are illustrated through a capability maturity model. Actual performance data is collected to validate the developed model. The results show that ERP is a hindrance on lean at the low maturity level. The influence on ERP only occurs with the mediator role of lean. ERP-based lean systems bring substantial benefits to organisations. Therefore, lean practices are a foundation upon which the full benefit of ERP can be received.
... AHP has been the decision making methodology which is helpful in making judgments by breaking down a complicated and complex problem into a multi-level hierarchy structure. It is one of the simplest and powerful methodologies used to address MCDM problems (Mohanavelu et al., 2017). AHP method is one of the best methodologies to prioritize various selection criteria. ...
Decision makers of various disciplines are facing challenges because of vast availability of options in the real world. Even though each and every decision made by a decision maker is being done with a great knowledge and conscience, the decision maker needs suitable support to choose the most favorable option to acquire great results in an agile environment. Supplier selection is imperative for an efficient supply chain management. Many industries are in need of effective decision making tools which aids them in valuable supplier selection. This paper proposes a model using Multi Criteria Decision Making (MCDM) tools viz., Grey Relational Analysis (GRA), Analytical Hierarchy Process (AHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS). GRA is used to shortlist the criteria from the available options, while AHP is used to assign weights to the criteria. The final supplier in the selection process is obtained using TOPSIS. The proposed GRA-AHP-TOPSIS model (GRAHP TOP) is used to analyze and formulate the important criteria and the applicability of the model is tested on a case of a small scale industry located in South India.
... The present study fills the gap in literature by conducting the assessment and measurement of the agile success factors using Two-way assessment and analytic hierarchy process (AHP) (Mohanavelu et al., 2017) to determine the maturity of the agile implementation in an enterprise. The measurement of the agile success factors will enable the practitioners to determine the maturity of agile implementation and make improvements based on the measurement result. ...
... The present study fills the gap in literature by conducting the assessment and measurement of the agile success factors using Two-way assessment and analytic hierarchy process (AHP) (Mohanavelu et al., 2017) to determine the maturity of the agile implementation in an enterprise. The measurement of the agile success factors will enable the practitioners to determine the maturity of agile implementation and make improvements based on the measurement result. ...
... Computer simulation palys an important role in analyzing engineering problems [17], [18], and [19]. In the past 2 decades, finite element anlaysis (FEA) has become an increasingly useful tool for the prediction of the stress [20], [21] and [22]. ...
In this paper, a flexible spot welding cell - which is flexible both at fixture and work cell level is developed to handle multiple Body-In-White (BIW) part varieties. The work-cell is a human-robot cooperative cell where the operator loads/unloads the parts on one side, whereas the robot concurrently performs welding operation on other side. The fixture is made modular and is reconfigured for change in part varieties. The flexibility of proposed work cell and fixture are investigated and validated by considering two different BIW spot weld assemblies. The performance of robot, cycle time estimation for the process, checking of fixtures, collision detection between weld gun and fixtures are evaluated in virtual environment. The flexible weld cell is proved to be compatible for both the BIW assemblies considered for study. The proposed concept shorten the design & fabrication time of fixture - squeezing the investment cost, assembly cost and floor space; besides reducing the cycle time and improving the robot utilization by 30% - 40% when compared to the conventional method.
