摘要:
In a method, device, and computer-readable medium for finite capacity scheduling, heuristic rules are applied in two integrated stages: Job Prioritization and Machine Selection. During Job Prioritization (“JP”), jobs are prioritized based on a set of JP rules which are machine independent. During Machine Selection (“MS”), jobs are scheduled for execution at machines that are deemed to be best suited based on a set of MS rules. The two-stage approach allows scheduling goals to be achieved for performance measures relating to both jobs and machines. For example, machine utilization may be improved while product cycle time objectives are still met. Two user-configurable options, namely scheduling model (job shop or flow shop) and scheduling methodology (forward, backward, or bottleneck), govern the scheduling process. A memory may store a three-dimensional linked list data structure for use in scheduling work orders for execution at machines assigned to work centers.
摘要:
To schedule the release of jobs from a pool of pending jobs, machine information and information about items to be processed are used to determine available machine capacity. Available machine capacity is allocated to jobs subject to multiple job release constraints. Allocation may be performed first for any pending jobs which were partially released during a previous time interval, and then to new jobs in decreasing order of determined job rank. If different operative constraints dictate different numbers of units of a job to be released, the minimum number of units meeting each constraint may be released. After the number of units to be released has been determined for a job, machine information is updated to account for available capacity consumed by the release of the selected number of units of the job. Updated information may be used for job release scheduling of the next job.
摘要:
To assess the sufficiency of a plurality of machines for processing a number of items, machine availability information indicative of availability of the machines for processing the items, machine capacity information indicative of a capacity of each of the machines for processing the items, and machine preference information indicative of a preference of each of the machines for processing the items are obtained. A capacity constraint, such as an upper limit of items to be processed during a time interval, is determined based on the machine availability information, machine capacity information and machine preference information. At least some of the machines are allocated to process at least some of the items based on the machine availability information, machine capacity information and machine preference information, subject to the capacity constraint. The resulting rough-cut capacity plan may be used to balance available capacity against required capacity.