The Integration of Process Planning and Shop Floor Scheduling in Small Batch Part Manufacturing

In this paper we explore possibilities to cut manufacturing leadtimes and to improve delivery performance in a small batch part manufacturing shop by integrating process planning and shop floor scheduling. Using a set of initial process plans (one for each order in the shop), we exploit a resource decomposition procedure to determine schedules to determine schedules which minimize the maximum lateness, given these process plans. If the resulting schedule is still unsatisfactory, a critical path analysis is performed to select jobs as candidates for alternative process plans. In this way, an excellent due date performance can be achieved, with a minimum of process planning and scheduling effort

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Scheduling with processing set restrictions : a survey

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A scheduling model for a knitting planning problem

In this paper we present two planning and scheduling models for a real problem of a textile industry that produces fine knitted goods. In both of them we develop plans to assist the knitting planning of one of three knitting subsections. In this problem we intend to assign and sequence, within a set of available and identical parallel machines, the demand associated with each component or garment part. This demand can be split in lots of smaller quantities and these lots can be independently produced at any time in one or more of the available machines. In the first model we develop a mixed integer programming (MIP) formulation and in the second one we develop network flow based models and a scheduling heuristic. The main advantage of the second model, in opposition to the first one, is the small computational resources needed to solve this huge and complex problem. We solve an instance generated in accordance with the characteristics of the real problem by the second model and present some performance measures

Scheduling in assembly type job-shops

Assembly type job-shop scheduling is a generalization of the job-shop scheduling problem to include assembly operations. In the assembly type job-shops scheduling problem, there are n jobs which are to be processed on in workstations and each job has a due date. Each job visits one or more workstations in a predetermined route. The primary difference between this new problem and the classical job-shop problem is that two or more jobs can merge to foul\u27 a new job at a specified workstation, that is job convergence is permitted. This feature cannot be modeled by existing job-shop techniques. In this dissertation, we develop scheduling procedures for the assembly type job-shop with the objective of minimizing total weighted tardiness. Three types of workstations are modeled: single machine, parallel machine, and batch machine. We label this new scheduling procedure as SB. The SB procedure is heuristic in nature and is derived from the shifting bottleneck concept. SB decomposes the assembly type job-shop scheduling problem into several workstation scheduling sub-problems. Various types of techniques are used in developing the scheduling heuristics for these sub-problems including the greedy method, beam search, critical path analysis, local search, and dynamic programming. The performance of SB is validated on a set of test problems and compared with priority rules that are normally used in practice. The results show that SB outperforms the priority rules by an average of 19% - 36% for the test problems. SB is extended to solve scheduling problems with other objectives including minimizing the maximum completion time, minimizing weighted flow time and minimizing maximum weighted lateness. Comparisons with the test problems, indicate that SB outperforms the priority rules for these objectives as well. The SB procedure and its accompanying logic is programmed into an object oriented scheduling system labeled as LEKIN. The LEKIN program includes a standard library of scheduling rules and hence can be used as a platform for the development of new scheduling heuristics. In industrial applications LEKIN allows schedulers to obtain effective machine schedules rapidly. The results from this research allow us to increase shop utilization, improve customer satisfaction, and lower work-in-process inventory without a major capital investment

A fast heuristic for a lot splitting and scheduling problem of a textile industry

In this paper we address a lot splitting and scheduling problem of a Textile factory that produces garment pieces. Each garment piece is made of a set of components that are produced on the knitting section of the company. The problem consists of finding a weekly production plan for the knitting section, establishing the quantities to produce of each component (organized in one or several lots), and where and when starting/completion times) to produce them. The main contribution of this work is the development of a constructive heuristic that generates automated knitting scheduling plans. The heuristic produces solutions very fast for a set of randomly generated instances based on real world data

Heuristics for scheduling a two-stage hybrid flow shop with parallel batching machines: application at a hospital sterilisation plant

The model of a two-stage hybrid (or flexible) flow shop, with sequence-independent uniform setup times, parallel batching machines and parallel batches has been analysed with the purpose of reducing the number of tardy jobs and the makespan in a sterilisation plant. Jobs are processed in parallel batches by multiple identical parallel machines. Manual operations preceding each of the two stages have been dealt with as machine setup with standardised times and are sequence-independent. A mixed-integer model is proposed. Two heuristics have been tested on real benchmark data from an existing sterilisation plant: constrained size of parallel batches and fixed time slots. Computation experiments performed on combinations of machines and operator numbers suggest balancing the two stages by assigning operators proportionally to the setup time requirements