Multi-Period Cell Loading and Job Sequencing in a Cellular Manufacturing System

In this paper, a multi-period cell loading problem is addressed, where the objectives are to minimise the number of tardy jobs (nT) in a multi-period planning horizon and optimise the scheduling of tardy jobs. Three cell loading and job scheduling strategies are proposed and tested with two newly developed mixed integer programming models. Additionally, three types of due dates (tight, medium and loose) and three different demand levels were considered. Finally, two tardy job assignment methods were proposed to observe the impact on nT. Case problems were solved based on minimising nT, Tmax and total tardiness (TT) objectives and cost sensitivity analysis was performed. Results indicated that, the first strategy, (early start allowance and tardy job assignment after each period) performed better in terms of nT. For the secondary objectives, tradeoffs were observed among different strategies depending on the type of due date, demand level and tardy job assignment method

Evaluation of Feedback among Multiple Scheduler Profiles in Fuzzy Genetic Scheduling

This paper extends the earlier studies conducted on multiple scheduler profile in fuzzy genetic scheduling. Multiple schedulers can set up individual fuzzy membership bounds which results in different evaluation of multi-objective problem of single machine scheduling. A new software application enables feedback among schedulers by applying seeding of individual scheduler\u27s population by best chromosomes from other scheduler\u27s population. Few experiments are performed on the aforementioned software application to evaluate the performance of the multi objective single machine scheduling problem by varying the level and frequency of feedback. More improvement is observed as the frequency of the feedback is increased but no significant improvement is observed when the level is increased

Group Scheduling in a Cellular Manufacturing Shop to Minimise Total Tardiness and nT: a Comparative Genetic Algorithm and Mathematical Modelling Approach

In this paper, family and job scheduling in a cellular manufacturing shop is addressed where jobs have individual due dates. The objectives are to minimise total tardiness and the number of tardy jobs. Family splitting among cells is allowed but job splitting is not. Two optimisation methods are employed in order to solve this problem, namely mathematical modelling (MM) and genetic algorithm (GA). The results showed that GA found the optimal solution for most of the problems with high frequency. Furthermore, the proposed GA is efficient compared to the MM especially for larger problems in terms of execution times. Other critical aspects of the problem such as family preemption only, impact of family splitting on common due date scenarios and dual objective scenarios are also solved. In short, the proposed comparative approach provides critical insights for the group scheduling problem in a cellular manufacturing shop with distinctive cases

A case of alcohol-related emphysematous cystitis

Emphysematous cystitis (EC) is a very rare urinary tract infectious disease that can be fatal if not treated. In general, it frequently occurs in diabetic women and is thought to be associated with gas-producing bacteria. Type 2 diabetes mellitus, immunosuppression, drugs (mostly steroids), neurogenic bladder and instrumentation are the major risk factors of this type of infection. We present a case of emphysematous cystitis in a 53-year-old male, in which the patient does not have any classical risk factors associated with EC other than alcohol consumption. To the best of our knowledge, the only case in the literature where this type of infection develops without a classical risk factor and negative urine culture. It is also one of the rare EC cases that may be associated with alcohol use

Manufacturing Cell Loading Rules and Algorithms for Connected Cells

Cellular Manufacturing (CM) can be defined as the implementation of group technology (GT) principles in a manufacturing environment. Situations that require decisions can be grouped together based on pre-selected, commonly shared criteria, and decision that applies to one situation in the group will apply to all of them in that group. The application of GT to manufacturing is achieved by identifying the items with either similar design or manufacturing characteristics and grouping them into families of like items. The benefits derived from CM include reduced work-in-process inventory and setup time, improved product quality, easier scheduling, better visibility of product schedule status, and quicker feedback of manufacturing deficiencies. The chapter discusses control of manufacturing cells, search priority primary product rule, secondary product rules, primary cell rules, number of feasible products (NFP), product mix (PM), and common cell capacity. The rules described are combined in different ways and 48 possible combinations are created. Twenty-four of the rule combinations are of cell priority type and the remaining 24 are of product priority type. © 1995, Elsevier B.V