Mixed-model sequencing to minimize utility work and the risk of conveyor stoppage

Article Abstract:

The mixed-model assembly line sequencing problem with constant cycle time is explored. Specifically, the study focuses on the problem of sequencing N products on an assembly line with the objectives of minimizing the risk of conveyor stoppage and lessening the total utility work. In a single station with inconsistent processing times, the problem is demonstrated to be NP-hard for each of the objectives. For a single station with two product types, each having a constant processing time, a sequence that minimizes both objectives can be determined in O(log N) computation time by developing an algorithm. Because the total utility work is minimized, the algorithm lessens the aggregate stoppage time between the arrival of the first product and the departure of the last product. The objective values obtained from the single station can also act as lower bounds for algorithm development or performance analysis for multiple-criterion, multiple-station problems.

Management, Conveyors, Assembly-line methods, Assembly lines, Conveying machinery

---

Operator assignment and the parametric preflow algorithm

Article Abstract:

The operator assignment problem pertains to the issue of maximizing the use of human operators assigned to perform operations using manufacturing systems in cases when the there is a given set of operations to accomplish, a specified work load for every one of these operations, and a given set of operators who are all skilled to perform certain aspects of the job. The primary motivation for resolving this problem is to be able to use the manufacturing system to its maximum capacity. The operator assignment problem, modelled as a network flow problem, was considered. The resolution of this problem treated as a parametric sequence of network maximum flow problems using Gallo, Grigoriadis and Tarjan's 'parametric preflow' was demonstrated.

---

Pathwise convexity and its relation to convergence of time-average derivatives

Article Abstract:

Infinitesimal perturbation analysis (IPA) is an approach used in the dealing with the problem of arriving at efficient derivative estimators for steady-state performance measures of stochastic systems. One theoretical aspect of the IPA has been causing much concern is its consistency. The issue was addressed by extending J.-Q. Hu's pathwise convexity method introduced in 1991. This approach was extended to demonstrate its effectivity in obtaining consistency of the infinitesimal perturbation analysis derivative estimator when applied to the G/G/1 queueing setting. Application of the method to stochastic storage theory and queuing networks was also demonstrated.

Convex domains, Perturbation (Mathematics)

Similar abstracts:

• Abstracts: Financial statement information and the pricing of earnings changes. Product pricing based on accounting costs
• Abstracts: Market segmentation, cannibalization, and the timing of product introductions. Why do retailers deal? An inventory explanation
• Abstracts: Seeking the institutional balance of power: avoiding the power of a balanced view. A psychoanalytic reading of hostile takeover events
• Abstracts: Boeing hit by machinists strike. Nation's rail workers go on strike. Congressional intervention halts railroad labor dispute
• Abstracts: On the idea of emancipation in management and organization studies. Managing change across boundaries: boundary-shaking practices

This website is not affiliated with document authors or copyright owners. This page is provided for informational purposes only. Unintentional errors are possible.