Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Multi-Objective Optimization Model for Integrated Process Planning and Job Shop Scheduling Using Cuckoo Search


Affiliations
1 Department of Mechanical Engineering, S V University College of Engineering, Tirupati, India
     

   Subscribe/Renew Journal


In manufacturing environment, unpredictable market changes results in modifications of part design and engineering specifications trigger frequent and costly fluctuations in process plans, setups, and machinery. Traditionally, process planning and scheduling were carried out in a sequential way. These approaches have become the obstacles to improve the productivity and responsiveness of the manufacturing system. Therefore, the integrated process planning and scheduling was introduced for significant improvements in manufacturing efficiency through eliminating or reducing scheduling conflicts. This paper presents Cuckoo Search (CS) based integrated process planning and scheduling which according to prescribed multi objectives such as minimizing process time, process cost, make span time and tardiness, could swiftly search for the optimal process plan and scheduling. The proposed methodology demonstrated with case study to validate its effectiveness and feasibility. It has proved from comparative study that the present method is flexible and robust.

Keywords

Integrated Process Planning and Scheduling, Precedence Relationship, Cuckoo Search, Makespan, Tardiness.
User
Subscription Login to verify subscription
Notifications
Font Size

  • Alting, L; Zhang, H: Computer-aided process planning: The state of- the-art survey, 'International Journal of Production Research', vol. 27, no. 4, 1989, 553–583.
  • John, M Usher; Royce, O Bowden: The application of genetic algorithm to operation sequencing for use in computer- aided process planning, ‘Computers ind. Engg’, vol. 30, no. 4, 1996, 999-1013.
  • Zhang, F; Zhang, YF; Nee, AYC: Using Genetic Algorithms in Process Planning for Job Shop Machining, ‘IEEE Transactions on Evolutionary Computation’, vol. 1, no. 4, November 1997.
  • Kiritsis, D; Neuendorf, KP; Xirouchakis, P: Petri net techniques for process planning cost estimation, ‘Advances in Engineering Software’, vol. 30, no. 6, 1999, 375-387.
  • Moon, Chiung; Lee, Young Hae; Gen, Mitsuo: Evolutionary Algorithm for Process Plan Selection with Multiple Objectives, ‘IEMS’, vol. 3, no. 2, 116-122, 2004.
  • Li, L; Fuh, JYH; Zhang, YF; Nee, AYC: Application of genetic algorithm to computer-aided process planning in distributed manufacturing environments, ‘Robotics and Computer-Integrated Manufacturing’, vol. 21, no. 6, 2005, 568-578.
  • Azab, Ahmed; ElMaraghy, Hoda: Sequential process planning: A hybrid optimal macro-level approach, ‘Journal of Manufacturing Systems’, vol. 26, no. 3-4, 2007, 147-160.
  • Dowluru Sreeramulu; Chilakalapalli Surya Prakasa Rao: Identification of Patterns in Genetic--‐Algorithm--‐Based Solutions for Optimization of Process--‐Planning Problems Using a Data Mining Tool, ‘International Journal of Applied Management and Technology’, vol. 10, no. 1, 2011.
  • Wanga, Jin Feng; Dub, BiQiang; Ding, HaiMin: A Modified Genetic Algorithm (GA) for optimization of process planning, ‘Journal Of Computers’, vol. 6, no. 7, 2011.
  • Aleksandar VUKOVIC; Mladen PERINIC; Milan IKONIC: Conceptual framework for creating customized modular CAPP system, ‘Eng. Rev’. 31-1, 2011, 35-43.
  • Nallakumarasamy, G; Srinivasan, PSS; Venkatesh Raja, K; Malayalamurthi, R: Optimization of operation sequencing in CAPP using Super hybrid Genetic Algorithms- Simulated Annealing Technique, ‘International Scholarly Research Network ISRN Mechanical Engineering’, 2011, Article ID 897498.
  • Mohammad Zahid Rayaz Khan; Dr Bajpai, AK: Optimization Of Process Planning Parameters Using Genetic Algorithm For Cylindrical Components, ‘International Journal of Engineering Research & Technology (IJERT)’, vol. 2, no. 7, ISSN: 2278-0181, 2013.
  • Kohansal, Morteza: Application Of Genetic Algorithm To Computer - Aided Planning For Optimization of Process Planning Problems Using A Data Mining Tool, ‘International Journal of Current Life Sciences’, vol. 4, no. 12, 13048-13062, 2014.
  • Wang, Jin Feng; Fan, Xiao Liang; Ding, Haimin: Application of Genetic Algorithm to computer aided process planning for optimization of process planning problems using a Data mining tool, ‘Hindawi Publishing Corporation The Scientific World Journal’, 2014, Article ID 294513.
  • Krishna Kanth, V; Sumanand, P; Sreeramulu, D: Optimization of process planning system for prismatic parts using ACO, ‘Journal of Material Science and Mechanical Engineering (JMSME)’, ISSN: 2393-9109; vol. 2, no. 5.
  • Mendes, Jorge Magalhaes: A two step optimization approach for job shop scheduling problem using a genetic algorithm.
  • Koblasa, František; Manlig, František; Jan Vavruška: Evolution Algorithm for Job Shop Scheduling Problem Constrained by the Optimization Timespan, ‘Applied Mechanics and Materials’, vol. 309, 2013, 350-357.
  • Abidi, Mustufa Haider; Al-Harkan, Ibrahim Mohamed; El-Tamimi, AM; Al-Ahmari, Abdulrahman: Ant Colony Optimization for Job shop scheduling to minimize the total weighted tardiness, ‘Proceedings of the 2014 Industrial and Systems Engineering Research Conference Y Guan and H Liao, eds’.
  • Demirel, Tufan; Ozkır, Vildan; Demirel, NihanCetin; Tasdelen, Belgin: A Genetic Algorithm Approach for Minimizing Total Tardiness in Parallel Machine Scheduling Problems, ‘Proceedings of the World Congress on Engineering’, vol II, 2011, WCE 2011, London, U.K.
  • Atay, Yilmaz; Kodaz, Halife; Optimization of job shop scheduling problems using modified clonal selection algorithm, ‘Turk J Elec Eng & Comp Sci’, 2014, 22: 1528 -1539.
  • Udaiyakumar, KC; Chandrasekaran, M: Application of Firefly Algorithm in Job Shop Scheduling Problem for Minimization of Makespan, ‘Procedia Engineering’, 97, 2014, 1798-1807.
  • Udaiyakumar, KC; Chandrasekaran, M: A Nature Inspired Firefly Heuristic Approach On Optimization Of Multi Objective Job hop Scheduling Problems, ‘Proceedings of Twelveth IRF International Conference’, 2014, Chennai, India, ISBN: 978-93-84209-48-3.
  • Moon, Chiung; Lee, Young Hae; Jeong, Chan Seok; Yun, Young Su: Integrated process planning and scheduling in a supply chain, ‘Computers & Industrial Engineering’, 54, 2008, 1048-1061.
  • Sharaf, Danah; Qahoush, Nicola; Haha, Nour; Al-Assi, Tala: Integration of Processing Planning and Scheduling in a Manufacturing Environment, ‘German Jordanian University’.
  • Leung, CW; Wong, TN; Mak, KL; Fung, RYK: Integrated process planning and scheduling by an agent-based ant colony optimization, ‘Computers & Industrial Engineering’, vol. 59, no. 1, 2010 166-180.
  • Li, Xinyu; Shao, Xinyu; Gao, Liang; Weirong Qian: An effective hybrid algorithm for integrated process planning and scheduling, ‘Int. J. Production Economics’, vol. 126, no. 2, 2010, 289-298.
  • Li, Xinyu; Zhang, Chaoyong; Gao, Liang; Li, Weidong; Shao, Xinyu: An agent-based approach for integrated process planning and scheduling, ‘Expert Systems with Applications’, vol. 37, no. 2, 2010, 1256-1264.
  • Li, Xinyu; Gao, Liang; Zhang, Chaoyong; Shao, Xinyu: A review on Integrated Process Planning and Scheduling, ‘Int. J. Manufacturing Research’, vol. 5, no. 2, 2010.
  • Srinivas, PS; Ramachandra Raju, V; Rao, CSP: Optimization of Process Planning and Scheduling using ACO and PSO Algorithms, ‘International Journal of Emerging Technology and Advanced Engineering’, ISSN 2250-2459, vol. 2, no. 10, 2012.
  • Demir, Halil Ibrahim; Uygun, Ozer; Cil, Ibrahim; Ipek, Mumtaz; Sari, Meral: Process Planning and Scheduling with SLK Due-Date Assignment where Earliness, Tardiness and Due-Dates are Punished, ‘Journal of Industrial and Intelligent Information’, vol. 3, no. 3, 2015.
  • Zhang, Shuai; Yu, Zhinan; Zhang, Wenyu; Yu, Dejian; Zhang, Dongping: Distributed Integration of Process Planning and Scheduling using an Enhanced Genetic Algorithm, ‘ICIC International © 2015’, ISSN: 1349-4198, 1587-1602.
  • Yang, Xin-She; Deb, Suash: Cuckoo search via Levy Flights, ‘Proc. Of World Congress on Nature & Biologically Inspired Computing’, IEEE Publications, USA, 2009, 210-214.
  • Marichelvam, MK; Prabaharan, T; Yang, XS: Improved cuckoo search algorithm for hybrid flow shop scheduling problems to minimize makespan, ‘Applied Soft Computing’, vol. 19, 2014, 93-101

Abstract Views: 230

PDF Views: 0




  • Multi-Objective Optimization Model for Integrated Process Planning and Job Shop Scheduling Using Cuckoo Search

Abstract Views: 230  |  PDF Views: 0

Authors

P. Vaidehi
Department of Mechanical Engineering, S V University College of Engineering, Tirupati, India
G. Padmanabhan
Department of Mechanical Engineering, S V University College of Engineering, Tirupati, India

Abstract


In manufacturing environment, unpredictable market changes results in modifications of part design and engineering specifications trigger frequent and costly fluctuations in process plans, setups, and machinery. Traditionally, process planning and scheduling were carried out in a sequential way. These approaches have become the obstacles to improve the productivity and responsiveness of the manufacturing system. Therefore, the integrated process planning and scheduling was introduced for significant improvements in manufacturing efficiency through eliminating or reducing scheduling conflicts. This paper presents Cuckoo Search (CS) based integrated process planning and scheduling which according to prescribed multi objectives such as minimizing process time, process cost, make span time and tardiness, could swiftly search for the optimal process plan and scheduling. The proposed methodology demonstrated with case study to validate its effectiveness and feasibility. It has proved from comparative study that the present method is flexible and robust.

Keywords


Integrated Process Planning and Scheduling, Precedence Relationship, Cuckoo Search, Makespan, Tardiness.

References