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Addresses the problem of implementing just‐in‐time (JIT) principlesin a processing shop organized in a batch manufacturing environment. Thefocus is on a processing shop…
Addresses the problem of implementing just‐in‐time (JIT) principles in a processing shop organized in a batch manufacturing environment. The focus is on a processing shop separated from an assembly shop by a parts store. Presents a multi‐criteria variant of the capacitated lot‐sizing model. The approach involves a pre‐emptive priority for JIT processing schedules, and a secondary priority for desirable load profiles. Solution properties are derived and used to facilitate the solution process for both the primary and secondary criterion models. Load profiles are assessed in the context of capacity requirements planning as well as from the alternative viewpoint of providing feedback to capacity planning through a consideration of capacity cushions. At both planning levels the approach is shown to allow optimum resource utilization without violating JIT principles. Presents optimization procedures, including a heuristic with an analytic performance bound.
The importance of reducing product lotsizes in converting traditional job shops into just‐in‐time (JIT) type manufacturing systems has been addressed in the literature…
The importance of reducing product lotsizes in converting traditional job shops into just‐in‐time (JIT) type manufacturing systems has been addressed in the literature. This paper presents a lotsize reduction model for closed stochastic production systems. The model is formulated based on an M/G/c queuing lotsize model. Product lotsize choice is related to all major components of job flow time: waiting time in queue, batch processing time, batch moving time, and finished goods warehousing time. The research is motivated by the fact that an optimal lotsize solution that minimizes only average job waiting time in the shop may not be optimal when the effects of job batch processing time, batch moving time, and batch warehousing time are also considered. There is no general closed form solution to the model due to the complexity of its nonlinear formulation. Based on the unique properties of the model, heuristic solution procedures are developed. The research demonstrates opportunities for shop managers to significantly reduce product lotsizes while minimizing total operating cost.
The objective of this research was to compare the behavior of two methods of managing an engineering change request (ECR) process, namely, perform changes as they occur or…
The objective of this research was to compare the behavior of two methods of managing an engineering change request (ECR) process, namely, perform changes as they occur or in a batch.
This comparison was accomplished by creating a computer model of a new product development (NPD) process and simulating ECR management. The model connects process design and process characteristics (teamwork, parallel activities) to process outcomes (development time, effort). The first method executes the ECR promptly and the rework is done as soon as the ECR is initiated. In the second method, ECRs are batched; in other words, a number of them are accumulated, and processing of the ECRs takes place when a batch of a certain size has accumulated. Thus, the change requests are grouped into a batch, and then, the section(s) of the process to effect the change(s) is (are) reworked.
Batching ECRs was found to be superior to doing them one at a time.
Future work should focus on refining the computer model and differentiating ECRs by assigning priorities to incoming ECRs.
For product development managers, processing ECRs in batches is preferable than attending to them on an individual basis. Nevertheless, in some situations ECRs require immediate attention. A mechanism will always be needed to deal with situations directly. Also, in terms of batching, ECRs could be processed in groups on a periodic basis. Periodically performing ECRs due to new design versions or prototypes in a timely manner is a good compromise between a random batch mode and doing them individually.
The paper shows that batch processing is superior to executing ECRs promptly as they are received. This result has been shown through the use of a computer model of NPD. To the authors' knowledge, no other studies have used computer modeling to study this problem.
This paper is aimed at comparing cellular manufacturing with focused cellular manufacturing. We define focused cellular manufacturing as a layout scheme that groups…
This paper is aimed at comparing cellular manufacturing with focused cellular manufacturing. We define focused cellular manufacturing as a layout scheme that groups components by end‐items and forms cells of machines to fabricate and assemble end‐items. It is not classified as a cellular manufacturing layout since it does not attempt to take advantage of process similarities. It also is not classified as a flow shop since there are no machines dedicated to individual operations and the machines are not arranged in a series. In addition, this research includes batching and assemble times in its criteria which few researchers in this area have done. The results indicate that the focused cellular manufacturing scheme has a batching advantage. This advantage out‐weighed the set‐up time reduction advantage of the cellular manufacturing scheme for average end‐item completion times and average work‐in‐process inventory levels. The cellular manufacturing scheme overcame the batching advantage only when there were small batch sizes or large set‐up time magnitudes.
Cellular and functional layouts were investigated under a varietyof real‐world conditions via a two‐stage computer simulation study. Inthe first stage, simulation models…
Cellular and functional layouts were investigated under a variety of real‐world conditions via a two‐stage computer simulation study. In the first stage, simulation models were developed for three actual companies. Six different cell formation procedures were used to develop the cellular layouts and CRAFT was used to develop the functional layout. The following six variables were used to measure shop performance: average flow time, maximum flow time, average distance travelled by a batch, average work‐in‐process level, the maximum level of work‐in‐process, and the longest average queue. Factors observed in the first stage of the study that appear to make cellular manufacturing less beneficial than might otherwise be expected were found to be small batch sizes, a small number of different machines the parts require in their processing, short processing times per part, the existence of bottleneck machines (i.e. machines with insufficient capacity), and the absence of natural part families (i.e. sets of parts with similar processing requirements). In the second stage of this study, earlier assumptions associated with sequence‐dependent setup times and move time delays were relaxed. These two parameters were identified as important factors as well.
The selection of part types for simultaneous processing in a Flexible Manufacturing System (FMS) is one of the most responsible phases of the short‐time production…
The selection of part types for simultaneous processing in a Flexible Manufacturing System (FMS) is one of the most responsible phases of the short‐time production planning. The batching approach to part type selection is more popular in practice but this leads to the requirement for a preliminary evaluation of the results obtained. Using simulation is a convenient, no‐risk and cheapest way to do this, which is shown and discussed in the paper. The objective of batching approach is to maximize the number of part types in a batch taking into account constraints on tool magazine capacity and tool type availability. Two alternative ways of assigning weights in the objective function of the part type selection model are explored to direct the search to a different set of part types. A procedure to determine the mix ratios of the selected part types is used so as to balance the aggregate machine workloads. The model aggregations have been accounted for in a simulation experiment conducted to evaluate the performance of the batching approach and to investigate the sensitivity of total makespan and machine utilizations.
In intelligent scheduling, parallel batch processing can reasonably allocate production resources and reduce the production cost per unit product. Hence, the research on a…
In intelligent scheduling, parallel batch processing can reasonably allocate production resources and reduce the production cost per unit product. Hence, the research on a parallel batch scheduling problem (PBSP) with uncertain job size is of great significance to realize the flexibility of product production and mass customization of personalized products.
The authors propose a robust formulation in which the job size is defined by budget constrained support. For obtaining the robust solution of the robust PBSP, the authors propose an exact algorithm based on branch-and-price framework, where the pricing subproblem can be reduced to a robust shortest path problem with resource constraints. The robust subproblem is transformed into a deterministic mixed integer programming by duality. A series of deterministic shortest path problems with resource constraints is derived from the programming for which the authors design an efficient label-setting algorithm with a strong dominance rule.
The authors test the performance of the proposed algorithm on the extension of benchmark instances in literature and compare the infeasible rate of robust and deterministic solutions in simulated scenarios. The authors' results show the efficiency of the authors' algorithm and importance of incorporating uncertainties in the problem.
This work is the first to study the PBSP with uncertain size. To solve this problem, the authors design an efficient exact algorithm based on Dantzig–Wolfe decomposition. This can not only enrich the intelligent manufacturing theory related to parallel batch scheduling but also provide ideas for relevant enterprises to solve problems.
A heuristic algorithm, designed for freeze‐drying operations in the foodprocessing industry, is developed for a multistage system with parallelmachines and resource…
A heuristic algorithm, designed for freeze‐drying operations in the food processing industry, is developed for a multistage system with parallel machines and resource constraints. The system is extremely complex owing to factors such as stage capacities, resource constraints and requirements, set‐up charges, product mix, order sizes, and co‐ordination of multiple stages. The primary objectives are meeting due dates, minimizing workflow time, and maximizing equipment utilization. The system is implemented to generate production schedules in a microcomputer‐based operating environment.
Cell formation design in cellular manufacturing systems (CMS) has beenthe focus of recent manufacturing research literature. A great amount ofresearch has been published…
Cell formation design in cellular manufacturing systems (CMS) has been the focus of recent manufacturing research literature. A great amount of research has been published addressing either technical issues (e.g. part‐machine grouping algorithms) or operational issues (e.g. planning and scheduling in the CMS). Research addressing strategic issues in cell formation design has been minimal. Addresses strategic considerations in cell formation design, specifically, the linkage and relationships between specific cell design issues and the firm′s competitive advantage in the marketplace. It is demonstrated that cell formation design decisions must be addressed in alignment with the firm′s strategic plan and manufacturing competitive priorities.
Presents an analytic framework for processing planning in industries where fixed batch sizes are common. The overall optimum processing plan is shown to be located on an…
Presents an analytic framework for processing planning in industries where fixed batch sizes are common. The overall optimum processing plan is shown to be located on an envelope between the optimum JIT plan and the optimum level plan. These concepts provide the framework for understanding the overall optimum plan, and the framework leads to an efficient heuristic. The approach is practical, illustrated by a case study from the food industry, which shows the place of overall optimum planning within the company’s planning system and its implications for company performance.