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Scheduling plays a pivotal role in the competitiveness of a job shop facility. The traditional job shop scheduling problem (JSSP) is centralized or semi-distributed. With the advent of Industry 4.0, there has been a paradigm shift in the manufacturing industry from traditional scheduling to smart distributed scheduling (SDS). The implementation of Industry 4.0 results in increased flexibility, high product quality, short lead times, and customized production. Smart/intelligent manufacturing is an integral part of Industry 4.0. The intelligent manufacturing approach converts renewable and nonrenewable resources into intelligent objects capable of sensing, working, and acting in a smart environment to achieve effective scheduling. This paper aims to provide a comprehensive review of centralized and decentralized/distributed JSSP techniques in the context of the Industry 4.0 environment. Firstly, centralized JSSP models and problem-solving methods along with their advantages and limitations are discussed. Secondly, an overview of associated techniques used in the Industry 4.0 environment is presented. The third phase of this paper discusses the transition from traditional job shop scheduling to decentralized JSSP with the aid of the latest research trends in this domain. Finally, this paper highlights futuristic approaches in the JSSP research and application in light of the robustness of JSSP and the current pandemic situation.
Raja Liaqait; Shermeen Hamid; Salman Warsi; Azfar Khalid. A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0. Sustainability 2021, 13, 7684 .
AMA StyleRaja Liaqait, Shermeen Hamid, Salman Warsi, Azfar Khalid. A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0. Sustainability. 2021; 13 (14):7684.
Chicago/Turabian StyleRaja Liaqait; Shermeen Hamid; Salman Warsi; Azfar Khalid. 2021. "A Critical Analysis of Job Shop Scheduling in Context of Industry 4.0." Sustainability 13, no. 14: 7684.
With the growing social and environmental concerns, the integration of sustainability in supplier selection and order allocation is of paramount importance. This research presents a holistic multi-phase decision-support framework to solve the sustainable supplier selection and order allocation problem for the multi-echelon supply chain. The framework comprises a multi-objective mixed-integer nonlinear programming mathematical model augmented with fuzzy multi-criteria decision making techniques and forecast demand. The various economic, environmental and social objectives were optimized for a multi-modal transportation network of a multi-echelon supply chain. The results of the mathematical model highlighted the impact of multi-modal transportation on the total cost and total travel time. The results also demonstrated the relationship between the multi-modal transport network and the environmental impact of the supply chain. The proposed multi-phase holistic decision support framework can be used in the comprehensive sustainability-based analysis of supply chains. GRAPHICAL ABSTRACT
Raja Awais Liaqait; Salman Sagheer Warsi; Mujtaba Hassan Agha; Taiba Zahid; Till Becker. A multi-criteria decision framework for sustainable supplier selection and order allocation using multi-objective optimization and fuzzy approach. Engineering Optimization 2021, 1 -22.
AMA StyleRaja Awais Liaqait, Salman Sagheer Warsi, Mujtaba Hassan Agha, Taiba Zahid, Till Becker. A multi-criteria decision framework for sustainable supplier selection and order allocation using multi-objective optimization and fuzzy approach. Engineering Optimization. 2021; ():1-22.
Chicago/Turabian StyleRaja Awais Liaqait; Salman Sagheer Warsi; Mujtaba Hassan Agha; Taiba Zahid; Till Becker. 2021. "A multi-criteria decision framework for sustainable supplier selection and order allocation using multi-objective optimization and fuzzy approach." Engineering Optimization , no. : 1-22.
In modern manufacturing industries, the importance of multi-objective optimization cannot be overemphasized particularly when the desired responses are differing in nature towards each other. With the emergence of new technologies, the need to achieve overall efficiency in terms of energy, output, and tooling is on the rise. Resultantly, endeavor is to make the machining process sustainable, productive, and efficient simultaneously. In this research, the effects of machining parameters (feed, cutting speed, depth of cut, and cutting condition including dry, wet, and cryogenic) were analyzed. Since sustainable production demands a balance between production quality and energy consumption, therefore, response parameters including specific cutting energy, tool wear, surface roughness, and material removal rate were considered. Taguchi-gray integrated approach was adopted in this study. Multi-objective function was developed using gray relational methodology, and its regression analysis was conducted. Response surface optimization was carried out to optimize the formulated multi-objective function and derive the optimum machining parameters. Concurrent responses were optimized with best-suited values of input parameters to make the most out of the machining process. Analysis of variance results showed that feed is the most effective parameter followed by cutting condition in terms of overall contribution in multi-objective function. The proposed optimum parameters resulted in improvement of tool wear and surface roughness by 30% and 22%, respectively, whereas specific cutting energy was reduced by 4%.
Muhammad Ali Khan; Syed Husain Imran Jaffery; Mushtaq Khan; Muhammad Younas; Shahid Ikramullah Butt; Riaz Ahmad; Salman Warsi. Multi-objective optimization of turning titanium-based alloy Ti-6Al-4V under dry, wet, and cryogenic conditions using gray relational analysis (GRA). The International Journal of Advanced Manufacturing Technology 2020, 106, 3897 -3911.
AMA StyleMuhammad Ali Khan, Syed Husain Imran Jaffery, Mushtaq Khan, Muhammad Younas, Shahid Ikramullah Butt, Riaz Ahmad, Salman Warsi. Multi-objective optimization of turning titanium-based alloy Ti-6Al-4V under dry, wet, and cryogenic conditions using gray relational analysis (GRA). The International Journal of Advanced Manufacturing Technology. 2020; 106 (9-10):3897-3911.
Chicago/Turabian StyleMuhammad Ali Khan; Syed Husain Imran Jaffery; Mushtaq Khan; Muhammad Younas; Shahid Ikramullah Butt; Riaz Ahmad; Salman Warsi. 2020. "Multi-objective optimization of turning titanium-based alloy Ti-6Al-4V under dry, wet, and cryogenic conditions using gray relational analysis (GRA)." The International Journal of Advanced Manufacturing Technology 106, no. 9-10: 3897-3911.
This study presents the development of a novel Specific Cutting Energy (SCE) based process map for turning of Al 6061 T6 alloy from conventional to high-speed machining range. The newly developed SCE map for turning process was compared with already published SCE maps for orthogonal machining. The comparison of maps revealed that SCE consumption trends observed in turning process are similar to those observed in orthogonal machining. Low values of SCE were observed at high cutting speeds and high feed rates that demonstrate the benefit of high-speed machining. Similar to the orthogonal machining SCE map, a high energy consumption zone named as “avoidance zone” was observed at high cutting speeds and low feed rates. Surface roughness analysis performed in the avoidance zone established the presence of built-up-edge on cutting inserts that not only resulted in high energy consumption but also deteriorated the surface finish of the machined part. Furthermore, statistical analysis of experimental data also revealed the significant effect of tool nose radius on SCE consumption in high-speed machining range. This significance of tool nose radius for SCE consumption has not been reported earlier in literature.
Salman Sagheer Warsi; Riaz Ahmad; Syed Husain Imran Jaffery; Mujtaba Hassan Agha; Mushtaq Khan. Development of specific cutting energy map for sustainable turning: a study of Al 6061 T6 from conventional to high cutting speeds. The International Journal of Advanced Manufacturing Technology 2020, 106, 2949 -2960.
AMA StyleSalman Sagheer Warsi, Riaz Ahmad, Syed Husain Imran Jaffery, Mujtaba Hassan Agha, Mushtaq Khan. Development of specific cutting energy map for sustainable turning: a study of Al 6061 T6 from conventional to high cutting speeds. The International Journal of Advanced Manufacturing Technology. 2020; 106 (7-8):2949-2960.
Chicago/Turabian StyleSalman Sagheer Warsi; Riaz Ahmad; Syed Husain Imran Jaffery; Mujtaba Hassan Agha; Mushtaq Khan. 2020. "Development of specific cutting energy map for sustainable turning: a study of Al 6061 T6 from conventional to high cutting speeds." The International Journal of Advanced Manufacturing Technology 106, no. 7-8: 2949-2960.
Productivity and economy are key elements of any sustainable manufacturing system. While productivity is associated to quantity and quality, economy focuses on energy efficient processes achieving an overall high output to input ratio. Machining of hard-to-cut materials has always posed a challenge due to increased tool wear and energy loss. Cryogenics have emerged as an effective means to improve sustainability in the recent past. In the present research the use of cooling conditions has been investigated as an input variable to analyze its effect on tool wear, specific cutting energy and surface roughness in combination with other input machining parameters of feed rate, cutting speed and depth of cut. Experimental design was based on Taguchi design of experiment. Analysis of Variance (ANOVA) was carried out to ascertain the contribution ratio of each input. Results showed the positive effect of coolant usage, particularly cryogenic, on process responses. Tool wear was improved by 33 % whereas specific cutting energy and surface roughness were improved by 10 % and 9 % respectively by adapting the optimum machining conditions.
Muhammad Ali Khan; Syed Husain Imran Jaffery; Mushtaq Khan; Muhammad Younas; Shahid Ikramullah Butt; Riaz Ahmad; Salman Warsi. Statistical analysis of energy consumption, tool wear and surface roughness in machining of Titanium alloy (Ti-6Al-4V) under dry, wet and cryogenic conditions. Mechanical Sciences 2019, 10, 561 -573.
AMA StyleMuhammad Ali Khan, Syed Husain Imran Jaffery, Mushtaq Khan, Muhammad Younas, Shahid Ikramullah Butt, Riaz Ahmad, Salman Warsi. Statistical analysis of energy consumption, tool wear and surface roughness in machining of Titanium alloy (Ti-6Al-4V) under dry, wet and cryogenic conditions. Mechanical Sciences. 2019; 10 (2):561-573.
Chicago/Turabian StyleMuhammad Ali Khan; Syed Husain Imran Jaffery; Mushtaq Khan; Muhammad Younas; Shahid Ikramullah Butt; Riaz Ahmad; Salman Warsi. 2019. "Statistical analysis of energy consumption, tool wear and surface roughness in machining of Titanium alloy (Ti-6Al-4V) under dry, wet and cryogenic conditions." Mechanical Sciences 10, no. 2: 561-573.
The objective of this study is to determine optimum machining parameters during high-speed turning (up to 1500 m/min) of Al 6061 T6 alloy. The chosen machining parameters optimize the trade-off between three competing responses: specific cutting energy, material removal rate, and surface roughness. These responses were first analyzed independently to establish their conflicting nature. Individual responses were then combined to formulate a multi-objective function using gray relational analysis augmented with analytic hierarchy process. Multi-objective function was optimized using regression analysis and response surface optimization. Analysis of variance results revealed cutting feed to be the most significant machining parameter affecting multi-objective function, followed by cutting speed and depth of cut. The proposed machining parameters resulted in reduction of specific cutting energy by 5% and an improvement of 33% in material removal rate while surface roughness remained unaffected.
Salman Sagheer Warsi; Mujtaba Hassan Agha; Riaz Ahmad; Syed Husain Imran Jaffery; Mushtaq Khan. Sustainable turning using multi-objective optimization: a study of Al 6061 T6 at high cutting speeds. The International Journal of Advanced Manufacturing Technology 2018, 100, 843 -855.
AMA StyleSalman Sagheer Warsi, Mujtaba Hassan Agha, Riaz Ahmad, Syed Husain Imran Jaffery, Mushtaq Khan. Sustainable turning using multi-objective optimization: a study of Al 6061 T6 at high cutting speeds. The International Journal of Advanced Manufacturing Technology. 2018; 100 (1-4):843-855.
Chicago/Turabian StyleSalman Sagheer Warsi; Mujtaba Hassan Agha; Riaz Ahmad; Syed Husain Imran Jaffery; Mushtaq Khan. 2018. "Sustainable turning using multi-objective optimization: a study of Al 6061 T6 at high cutting speeds." The International Journal of Advanced Manufacturing Technology 100, no. 1-4: 843-855.
Specific cutting energy consumption in high-speed orthogonal machining of Al 6061-T6 alloy has been analyzed in this work. The evaluated values of specific cutting energy are presented as an energy map developed over a cutting speed-undeformed chip thickness grid. Different regions characterized by energy consumption have been defined on the developed map. Very low values of specific cutting energy (up to 0.32 J/mm3) were observed for Al 6061-T6 alloy while machining over the cutting speed of 1500 m/min. Such low energy values have not been reported earlier in literature and they demonstrate another benefit of high-speed machining along with better surface finish, low cutting forces, and high production rate. The developed energy map revealed the presence of a very high energy zone in the midst of a comparatively low energy consumption region. A detailed analysis was performed to investigate the formation of this high energy zone or “avoidance zone.” The analysis of results revealed excessive built-up edge formation within this zone.
Salman Sagheer Warsi; Syed Husain Imran Jaffery; Riaz Ahmad; Mushtaq Khan; Mujtaba Hassan Agha; Liaqat Ali. Development and analysis of energy consumption map for high-speed machining of Al 6061-T6 alloy. The International Journal of Advanced Manufacturing Technology 2018, 96, 91 -102.
AMA StyleSalman Sagheer Warsi, Syed Husain Imran Jaffery, Riaz Ahmad, Mushtaq Khan, Mujtaba Hassan Agha, Liaqat Ali. Development and analysis of energy consumption map for high-speed machining of Al 6061-T6 alloy. The International Journal of Advanced Manufacturing Technology. 2018; 96 (1-4):91-102.
Chicago/Turabian StyleSalman Sagheer Warsi; Syed Husain Imran Jaffery; Riaz Ahmad; Mushtaq Khan; Mujtaba Hassan Agha; Liaqat Ali. 2018. "Development and analysis of energy consumption map for high-speed machining of Al 6061-T6 alloy." The International Journal of Advanced Manufacturing Technology 96, no. 1-4: 91-102.
The major source of environment and economic impact of machine tools has been attributed to their energy consumption. This article, therefore, proposes a novel energy mapping approach to evaluate specific cutting energy consumption with respect to cutting parameters. Unlike the studies presented earlier, which are machine-tool-specific, this study focuses on the basic tool–workpiece interaction for energy consumption analysis. The presented energy map reveals different energy consumption regions at varying machining parameters (feed and speed) during orthogonal machining of Al 6061-T6 alloy. The chip formation analysis indicates a strong correlation with the different energy consumption regions identified on the energy map. It has been observed that feed is the major contributing factor towards shear plane angle during chip formation as compared to cutting speed. Therefore, increasing feed results in a higher shear angle and consequently lowering the specific cutting energy as indicated on the energy map. Selection of machining parameters corresponding to the lowest specific cutting energy consumption region, as identified on the energy map, can result in energy savings up to 27% per kg of material removed. The developed map can be used for selection of suitable energy-efficient cutting parameters.
Salman Warsi; Syed Husain Imran Jaffery; Riaz Ahmad; Mushtaq Khan; Liaqat Ali; Mujtaba Hassan Agha; Sohail Akram. Development of energy consumption map for orthogonal machining of Al 6061-T6 alloy. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 2017, 232, 2510 -2522.
AMA StyleSalman Warsi, Syed Husain Imran Jaffery, Riaz Ahmad, Mushtaq Khan, Liaqat Ali, Mujtaba Hassan Agha, Sohail Akram. Development of energy consumption map for orthogonal machining of Al 6061-T6 alloy. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 2017; 232 (14):2510-2522.
Chicago/Turabian StyleSalman Warsi; Syed Husain Imran Jaffery; Riaz Ahmad; Mushtaq Khan; Liaqat Ali; Mujtaba Hassan Agha; Sohail Akram. 2017. "Development of energy consumption map for orthogonal machining of Al 6061-T6 alloy." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 232, no. 14: 2510-2522.
In this research work, Aluminum alloy Al6061-T6 was machined in order to investigate the chip morphology at different cutting parameters. Chip morphology with different shapes and sizes affects various aspects such as cutting force, chatter stability and cutting temperature which in turn influences workpiece surface quality, tool life, and machining efficiency. Orthogonal cutting experiments were carried out with the CCMW 09 T3 04-H13A uncoated carbide tool in the cutting speed range of 250-1,000 m/min and feed rate of 0.1-0.4 mm/r to obtain the chip thicknesses and the shear angles. Commercially available software Abaqus/Explicit was used to simulate a 2D orthogonal model. The simulation results were found to be in close agreement with the experimental results and showed that chip thickness decreased with increasing cutting speed whereas shear angle increased with the increase of cutting speed.
Sohail Akram; Husain Imran; Mushtaq Khan; Aamir Mubashar; Salman Warsi; Umair Riaz. A numerical investigation and experimental validation on chip morphology of Aluminum Alloy 6061 during orthogonal machining. 2016 Moratuwa Engineering Research Conference (MERCon) 2016, 331 -336.
AMA StyleSohail Akram, Husain Imran, Mushtaq Khan, Aamir Mubashar, Salman Warsi, Umair Riaz. A numerical investigation and experimental validation on chip morphology of Aluminum Alloy 6061 during orthogonal machining. 2016 Moratuwa Engineering Research Conference (MERCon). 2016; ():331-336.
Chicago/Turabian StyleSohail Akram; Husain Imran; Mushtaq Khan; Aamir Mubashar; Salman Warsi; Umair Riaz. 2016. "A numerical investigation and experimental validation on chip morphology of Aluminum Alloy 6061 during orthogonal machining." 2016 Moratuwa Engineering Research Conference (MERCon) , no. : 331-336.
Recent researches in machining have revealed that electricity consumption of machine tools accounts for 90% of their environmental impact. Therefore, minimization of energy consumption will not only enhance its economic viability but will also reduce CO2 emissions. Most energy consumption studies present in literature focus on machining at low speeds (up to 500 m/min), whereas the specific cutting energy and power consumption trends at higher speeds have not been thoroughly investigated. This study analyses energy consumption in the machining of aluminium alloy Al-6061 T6 at high cutting speeds (up to 1000m/min and feeds up to 0.4 mm/rev). Full factorial experiments with three replicates were performed for orthogonal machining of AL-6061 T6 alloy which is one of the widely used materials in aerospace, automobiles, defence, sports and biomedical industries. A strict power measurement protocol was followed in accordance with CO2PE! (Cooperative Effort in Process Emission) proposed taxonomy. All the experiments were performed by unused inserts, therefore tool wear effect was not considered for power and energy calculations. The results were analysed using ANOVA and the contribution of speed and feed on energy consumption were quantified. Energy consumption map was prepared for varied speeds and feeds that revealed the presence of the optimum energy zones.
Salman S. Warsi; Hussain I. Jaffery; Riaz Ahmad; Mushtaq Khan; Sohail Akram. Analysis of Power and Specific Cutting Energy Consumption in Orthogonal Machining of Al 6061-T6 Alloys at Transitional Cutting Speeds. Volume 3: Biomedical and Biotechnology Engineering 2015, 1 .
AMA StyleSalman S. Warsi, Hussain I. Jaffery, Riaz Ahmad, Mushtaq Khan, Sohail Akram. Analysis of Power and Specific Cutting Energy Consumption in Orthogonal Machining of Al 6061-T6 Alloys at Transitional Cutting Speeds. Volume 3: Biomedical and Biotechnology Engineering. 2015; ():1.
Chicago/Turabian StyleSalman S. Warsi; Hussain I. Jaffery; Riaz Ahmad; Mushtaq Khan; Sohail Akram. 2015. "Analysis of Power and Specific Cutting Energy Consumption in Orthogonal Machining of Al 6061-T6 Alloys at Transitional Cutting Speeds." Volume 3: Biomedical and Biotechnology Engineering , no. : 1.