A Heuristic Scheduling Algorithm for Minimizing Makespan and Idle Time in a Nagare Cell

Adopting a focused factory is a powerful approach for today manufacturing enterprise. This paper introduces the basic manufacturing concept for a struggling manufacturer with limited conventional resources, providing an alternative solution to cell scheduling by implementing the technique of Nagare cell. Nagare cell is a Japanese concept with more objectives than cellular manufacturing system. It is a combination of manual and semiautomatic machine layout as cells, which gives maximum output flexibility for all kind of low-to-medium- and medium-to-high- volume productions. The solution adopted is to create a dedicated group of conventional machines, all but one of which are already available on the shop floor. This paper focuses on the development of heuristic scheduling algorithm in step-by-step method. The algorithm states that the summation of processing time of all products on each machine is calculated first and then the sum of processing time is sorted by the shortest processing time rule to get the assignment schedule. Based on the assignment schedule Nagare cell layout is arranged for processing the product. In addition, this algorithm provides steps to determine the product ready time, machine idle time, and product idle time. And also the Gantt chart, the experimental analysis, and the comparative results are illustrated with five ( 1 × 8 to 5 × 8 ) scheduling problems. Finally, the objective of minimizing makespan and idle time with greater customer satisfaction is studied through.

[1]  X. X. Wang,et al.  An ant colony optimization algorithm for scheduling virtual cellular manufacturing systems , 2007, Int. J. Comput. Integr. Manuf..

[2]  V. Selladurai,et al.  Optimization and implementation of cellular manufacturing system in a pump industry using three cell formation algorithms , 2007 .

[3]  Chelliah Sriskandarajah,et al.  Scheduling algorithms for flexible flowshops: Worst and average case performance , 1988 .

[4]  Hamilton Emmons,et al.  Scheduling families of jobs with setup times , 1997 .

[5]  Katsuhisa Ohno,et al.  ANALYSIS AND OPTIMIZATION OF A U-SHAPED PRODUCTION LINE , 1997 .

[6]  Rasaratnam Logendran,et al.  Machine duplication and part subcontracting in the presence of alternative cell locations in manufacturing cell design , 2000, J. Oper. Res. Soc..

[7]  N. Nakamura,et al.  Group production scheduling for minimum total tardiness Part(I) , 1978 .

[8]  Saadettin Erhan Kesen,et al.  A mixed integer programming formulation for scheduling of virtual manufacturing cells (VMCs) , 2010 .

[9]  Andrew Kusiak,et al.  Intelligent Manufacturing Systems , 1990 .

[10]  M. Selim Akturk,et al.  Cellular manufacturing system design using a holonistic approach , 2000 .

[11]  Li Ma,et al.  A two-stage mathematical approach for the design of Virtual Manufacturing Cells , 2009 .

[12]  John M. Kay,et al.  Group Technology and Cellular Manufacturing , 1998 .

[13]  Fong-Yuen Ding,et al.  Heuristics for scheduling flexible flow lines , 1994 .

[14]  R. A. Dudek,et al.  A Heuristic Algorithm for the n Job, m Machine Sequencing Problem , 1970 .

[15]  I Mahdavi,et al.  FLEXIBLE FLOWSHOP SCHEDULING WITH EQUAL NUMBER OF UNRELATED PARALLEL MACHINES; TECHNICAL NOTE , 2011 .

[16]  J. M. Kay,et al.  Group technology and cellular manufacturing: state-of-the-art synthesis of research and practice , 1998 .

[17]  Nancy Lea Hyer,et al.  Research issues in cellular manufacturing , 1987 .

[18]  Jung Woo Jung,et al.  Flowshop-scheduling problems with makespan criterion: a review , 2005 .

[19]  Kenneth R. Baker,et al.  Scheduling the production of components at a common facility , 1988 .

[20]  Rasaratnam Logendran,et al.  Combined heuristics for bi-level group scheduling problems , 1995 .

[21]  T. T. Narendran,et al.  Heuristics and sequence-dependent set-up jobs in flow line cells , 2003 .

[22]  Pius J. Egbelu,et al.  Job scheduling in a group technology environment for a single facility , 1985 .

[23]  Shahrukh A. Irani,et al.  Next Generation Factory Layouts: Research Challenges and Recent Progress , 2002, Interfaces.

[24]  John B. Jensen,et al.  Machine dedication and process flexibility in a group technology environment , 1996 .

[25]  Kenneth R. Baker,et al.  Scheduling Groups of Jobs on a Single Machine , 1995, Oper. Res..

[26]  Tadeusz Sawik,et al.  Mixed integer programming for scheduling flexible flow lines with limited intermediate buffers , 2000 .

[27]  D.G.M. Brooks,et al.  The competitive edge in developing a traditional manufacturing business , 1994 .

[28]  D. S. Palmer Sequencing Jobs Through a Multi-Stage Process in the Minimum Total Time—A Quick Method of Obtaining a Near Optimum , 1965 .

[29]  Elin M. Wicks,et al.  Designing cellular manufacturing systems with dynamic part populations , 1999 .

[30]  R. Radharamanan A heuristic algorithm for group scheduling , 1986 .

[31]  Jatinder N. D. Gupta,et al.  Flowshop scheduling with set-up, processing and removal times separated , 1991 .

[32]  S. M. Johnson,et al.  Optimal two- and three-stage production schedules with setup times included , 1954 .

[33]  Jatinder N. D. Gupta,et al.  Scheduling a flowline manufacturing cell with sequence dependent family setup times , 2000, Eur. J. Oper. Res..

[34]  E. Ignall,et al.  Application of the Branch and Bound Technique to Some Flow-Shop Scheduling Problems , 1965 .

[35]  Rajiv M. Gupta,et al.  An examination of the dynamic behaviour of part-families in group technology , 1982 .

[36]  Nancy Lea Hyer,et al.  Cellular manufacturing in the U.S. industry: a survey of users , 1989 .

[37]  Dileep R. Sule,et al.  Sequencing n jobs on two machines with setup, processing and removal times separated , 1982 .

[38]  Rasaratnam Logendran,et al.  Minimizing the makespan of a group scheduling problem: a new heuristic , 1991 .