Reference number : GC-2017-Q2-00322, amendment number : , agreement type : G, recipient legal name : Defersha, Fantahun (University of Guelph), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Engage Grants for Universities, program name french : Subventions d'engagement partenarial pour les universités, program purpose english : A general description of scheduling is the allocation of resources over time to perform a collection of tasks. In_x000D_
literature, this critical approach to scheduling problems has been formalized as scheduling theory. Scheduling_x000D_
in practice, however, varies greatly between different companies with no definitive model of "real world"_x000D_
scheduling available to aid manufacturing industries. The lack of attention to the realities of scheduling by the_x000D_
research community has given the rise to the so-called ''gap" between theory and practice. Many researchers_x000D_
were simply optimistic that their new and improved heuristics would be embedded in a computer systems by_x000D_
scheduling software vendors, which would then in turn be widely used in job shops. However, most job shop_x000D_
style factories are still scheduling and planning the old-fashioned way using a collection of dispatching rules_x000D_
that are far from being optimal. It is apparent that theoretical research in developing algorithms for scheduling_x000D_
has done little to improve the scheduling practice. This has resulted in many industries not having scheduling_x000D_
systems very tailored to their needs. The research problem identified in the collaborating industry involves the_x000D_
scheduling of large numbers of orders in the stamping area of the manufacturing plant. Complexity arises from_x000D_
the many inter-dependencies of the manufacturing operations and their requirements. The scheduling_x000D_
framework and the solution methodology to be develop is a hybrid approach that combines Job-Dispatching_x000D_
rules from traditional scheduling theory and Event-Scheduling/Time-Advance algorithm (ESTA) from the_x000D_
theory of discrete event systems simulation. Job-dispatching rule are simple to use. However, they lack the_x000D_
ability to handle complex operational logic and do not provide schedule. To obtain actual production schedule_x000D_
using these simple dispatching rules, in this research, we will apply the concept of discrete event simulation. In_x000D_
doing so, the operational logic of the manufacturing systems will be modeled in a computer program. The_x000D_
dispatching rules will then be executed in a simulated time using ESTA algorithm of discrete event systems_x000D_
simulation to generate production schedules., program purpose french : A general description of scheduling is the allocation of resources over time to perform a collection of tasks. In_x000D_
literature, this critical approach to scheduling problems has been formalized as scheduling theory. Scheduling_x000D_
in practice, however, varies greatly between different companies with no definitive model of "real world"_x000D_
scheduling available to aid manufacturing industries. The lack of attention to the realities of scheduling by the_x000D_
research community has given the rise to the so-called ''gap" between theory and practice. Many researchers_x000D_
were simply optimistic that their new and improved heuristics would be embedded in a computer systems by_x000D_
scheduling software vendors, which would then in turn be widely used in job shops. However, most job shop_x000D_
style factories are still scheduling and planning the old-fashioned way using a collection of dispatching rules_x000D_
that are far from being optimal. It is apparent that theoretical research in developing algorithms for scheduling_x000D_
has done little to improve the scheduling practice. This has resulted in many industries not having scheduling_x000D_
systems very tailored to their needs. The research problem identified in the collaborating industry involves the_x000D_
scheduling of large numbers of orders in the stamping area of the manufacturing plant. Complexity arises from_x000D_
the many inter-dependencies of the manufacturing operations and their requirements. The scheduling_x000D_
framework and the solution methodology to be develop is a hybrid approach that combines Job-Dispatching_x000D_
rules from traditional scheduling theory and Event-Scheduling/Time-Advance algorithm (ESTA) from the_x000D_
theory of discrete event systems simulation. Job-dispatching rule are simple to use. However, they lack the_x000D_
ability to handle complex operational logic and do not provide schedule. To obtain actual production schedule_x000D_
using these simple dispatching rules, in this research, we will apply the concept of discrete event simulation. In_x000D_
doing so, the operational logic of the manufacturing systems will be modeled in a computer program. The_x000D_
dispatching rules will then be executed in a simulated time using ESTA algorithm of discrete event systems_x000D_
simulation to generate production schedules., agreement title english : Production and Manpower Scheduling, agreement title french : Production and Manpower Scheduling, agreement number : EGP, agreement value : 23865.0, agreement start date : 2017-08-23, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada