Decision Making in Manufacturing and Services
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ISSN 1896-8325
e-ISSN: 2300-7087
Issue Date
2008
Volume
Vol. 2
Number
No. 1/2
Description
Journal Volume
Decision Making in Manufacturing and Services
Vol. 2 (2008)
Projects
Pages
Articles
CP-driven production process planning in multiproject environment
(2008) Banaszak, Zbigniew; Bocewicz, Grzegorz; Bach, Irena
The way enterprise capabilities are used decides about its competitiveness among other ones. In that context modeling aimed at production tasks allocation planning plays a crucial role especially at concurrently executed production orders. The introduced reference model employing constraint programming (CP) paradigm describes both an enterprise and a set of project-like production orders. Moreover, encompassing consumer orders requirements and available production capabilities, the model provides the formal framework allowing one to develop a class of decision support systems aimed at interactive production process planning subject to multiproject environment constraints. In that context our contribution is a knowledge-based and CP-driven approach to resource allocation assuming precise character of decision variables. The conditions sufficient for deadlock avoidance are the main goal. The conditions delivered provide formal framework for developing a task oriented Decision Support Tool for Project Portfolio Prototyping (DST4P, Banaszak 2006). The tool provides a prompt and interactive service to a set of routine queries formulated either in straight or reverse way.
A transfer line balancing problem by heuristic methods: industrial case studies
(2008) Guschinskaya, Olga; Dolgui, Alexandre
The paper deals with the problem of optimal configuration of a type of transfer lines which are equipped with transfer machines. Such machines perform operations with standard modular spindle heads which are activated sequentially. All operations assigned to the same spindle head (block of operations) are executed simultaneously by a set of tools fixed at the spindle head. The quantity of machines and spindle heads used to produce a part with the given productivity rate defines the final cost of the transfer line which must be minimized. To minimize this cost, a combinatorial problem of operations assignment to blocks and machines must be solved. The solution must provide a desired productivity (cycle time), it must also satisfy precedence and compatibility constraints. In this paper, we suggest improved versions of FSIC heuristic algorithm in order to help line designers to solve real-scale industrial problems. Results of computational experiments obtained for industrial cases are presented.
Partial coordination may increase overall costs in supply chains
(2008) Kaczmarczyk, Waldemar
This paper presents a computational study to evaluate the impact of coordinating production and distribution planning in a two-level industrial supply chain. Three planning methods are compared. The first emulates the traditional way of planning. The two other coordinate plans of the supplier and of all the buyers according to the Vendor Managed Inventory (VMI) approach. The monolithic method solves a single model describing the entire optimization problem. The sequential method copies the imperfect VMI practice. All three methods are implemented by means of Mixed Integer Programming models. The results presented prove that the right choice of planning method is very important for overall cost of the supply chain. In contrast to the previous research, it turned out that information sharing without full coordination may even lead to increase in the overall cost. For some companies applying the VMI approach, developing exact models and solving them almost optimally may therefore be very important.
Developing and deploying electronics assembly line optimization tools: a Motorola case study
(2008) Tirpak, Thomas M.
The assignment of workloads to production equipment is one category of planning decision for an electronics assembly factory. In practice, line balancing requires not only selecting machines with sufficient placement accuracy and feeder capacity, but also addressing a host of other operational objectives and constraints. Motorola Labs led a multi-year effort to apply mathematical programming to balance a variety of production mix and volume scenarios. By representing the optimization problem as a specially structured, mixed linear-integer program, we were able to incorporate a high degree of reality in the model, simultaneously optimizing fixed setups, handling custom parts, maximizing machine uptime, and mitigating secondary bottlenecks. This paper presents the story of how we developed and deployed a software solution that significantly improved assembly cycle times, setup changeovers, and overall factory productivity, saving the company tens of millions of dollars.
A loss function for box-constrained inverses problems
(2008) Yoneda, Kiyoshi
A loss function is proposed for solving box-constrained inverse problems. Given causality mechanisms between inputs and outputs as smooth functions, an inverse problem demands to adjust the input levels to make the output levels as close as possible to the target values; box-constrained refers to the requirement that all outcome levels remain within their respective permissible intervals. A feasible solution is assumed known, which is often the status quo. We propose a loss function which avoids activation of the constraints. A practical advantage of this approach over the usual weighted least squares is that permissible outcome intervals are required in place of target importance weights, facilitating data acquisition. The proposed loss function is smooth and strictly convex with closed-form gradient and Hessian, permitting Newton family algorithms. The author has not been able to locate in the literature the Gibbs distribution corresponding to the loss function. The loss function is closely related to the <i>generalized matching law</i> in psychology.