Scheduling a general flexible manufacturing system to minimize tardiness related costs

Includes bibliographical references (p. 59-60)

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the classical simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.Comment: 18 pages, 1 figur

A line-balancing strategy for designing flexible assembly systems

We present a rough-cut analysis tool that quickly determines a few potential cost-effective designs at the initial design stage of flexible assembly systems (FASs) prior to a detailed analysis such as simulation. It uses quantitative methods for selecting and configuring the components of an FAS suitable for medium to high volumes of several similar products. The system is organized as a series of assembly stations linked with an automated material-handling system moving parts in a unidirectional flow. Each station consists of a single machine or of identical parallel machines. The methods exploit the ability of flexible hardware to switch almost instantaneously from product to product. Our approach is particularly suitable where the product mix is expected to be stable, since we combine the hardware-configuration phase with the task-allocation phase.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45513/1/10696_2004_Article_BF00167513.pd

Sodium balance in adult atlantic salmon (Salmo salar L.) during migration into neutral and acid fresh water

1. In sea-water, adult salmon (S. salar) exchange an average of 12.6% of total body sodium/hr. 2. Following transfer to fresh water sodium uptake follows Michaelis-Menton kinetics. Fmax = 2.40 mmol Na/1 ECF/hr, Km = 0.26 mmol Na/1. The uptake system is fully activated immediately following transfer to fresh water. 3. Post smolts adapted to sea-water for 3 months take up sodium at only one third of the rate of adult fish following return to fresh water. 4. The concentration of prolactin in the plasma is low in sea-water adapted fish and does not rise during the first 8 hr in fresh water. 5. At pH 5 sodium uptake is reduced by almost 90%, even in the absence of aluminium, but recovers immediately on return to neutral water. 6. At pH 5 and 20 μmol Al/1 there is little further effect on sodium uptake but after 6 hr in aluminium the inhibition of sodium uptake continues after return to neutral aluminium fresh water and uptake is only 50% of normal 24 hr later

Due date based scheduling in a general flexible manufacturing system

Dynamic scheduling of manufacturing systems for due date based objectives has received considerable attention from practitioners and researchers due to the importance of meeting due dates in most industries. Research investigations have focused primarily on the relative effectiveness of various dispatching rules in job shops. These rules operate by prioritizing jobs using a “criticality index” based on job and system status. Jobs are then scheduled from most critical to least, with the indexes typically being updated as the system changes.This study considers two important issues which have not been addressed previously in the literature. First, we investigate the impact of unequal machine workloads on the relative effectiveness of dispatching rules. This is significant because workloads are likely to be unbalanced in most real systems. While it is clear, intuitively, that this imbalance in machine workloads is likely to deteriorate system performance, it is not obvious whether the superiority of certain dispatching rules established in earlier studies for balanced workloads is carried forward to this case. We show that the performance of different dispatching rules does indeed depend upon the degree of workload imbalance. We also propose and test a scheduling procedure which performs well in both balanced and unbalanced systems.Next, we develop a scheduling approach which shows promise as being an improved alternative to the use of dispatching rules. This approach decomposes the dynamic scheduling problem into a series of static problems.These static problems are then solved using an optimum‐seeking method, and the solutions are implemented on a rolling basis. We show through a simulation experiment that adopting this approach over dispatching rules leads to an improvement in the overall solution quality, even in a dynamic environment.The two very practical implications of our study are: (1) that commonly used dispatching rules in job shops or automated manufacturing systems may not be the best approach when capacity utilization is unbalanced (2) a job shop or automated manufacturing system would likely benefit from implementing optimal‐seeking scheduling rules instead of the traditional job dispatching rules.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146830/1/joom115.pd

Beam-ACO Applied to Assembly Line Balancing

Assembly line balancing concerns the design of assembly lines for the manufacturing of products. In this paper we consider the time and space constrained simple assembly line balancing problem with the objective of minimizing the number of necessary work stations. This problem is denoted by TSALBP-1 in the literature. For tackling this problem we propose a Beam-ACO approach, which is an algorithm that results from hybridizing ant colony optimization with beam search. The experimental results show that our algorithm is a state-of-the-art metaheuristic for this problem