Approximations for fork/join systems with inputs from multi-server stations.

Fork/join stations are commonly used to model synchronization constraints in queuing network models of computer and manufacturing systems. This paper presents an exact analysis of a fork/join station in a closed queuing network with inputs from multi-server stations with two-phase Coxian service distributions. The underlying queue length process is analyzed exactly to determine performance measures such as through put, and distributions of the queue length at the fork/join station. By choosing suitable parameters for the two-phase Coxian distributions, the effect of variability in inputs on system performance is studied. The study reveals that for several system configurations, analysis of the simpler system with exponential inputs provides efficient approximations for performance measures. Both, the exact analysis and the simple approximations of fork/join systems constitute useful building blocks for developing efficient methods for analyzing large queuing networks with fork/join stations.queueing; fork/join; synchronization; assembly systems; closed queuing networks;

Queueing theory and operations management.

Management; Theory;

Sustainable R&D portfolio assessment.

Research and development portfolio management is traditionally technologically and financially dominated, with little or no attention to the sustainable focus, which represents the triple bottom line: not only financial (and technical) issues but also human and environmental values. This is mainly due to the lack of quantified and reliable data on the human aspects of product/service development: usability, ecology, ethics, product experience, perceived quality etc. Even if these data are available, then consistent decision support tools are not ready available. Based on the findings from an industry review, we developed a DEA model that permits to support strategic R&D portfolio management. We underscore the usability of this approach with real life examples from two different industries: consumables and materials manufacturing (polymers).R&D portfolio management; Data envelopment analysis; Sustainable R&D;

The consequences of time-phased order releases on two M/M/1 queues in series.

A key characteristic of MRP applications includes the coordination of assembly and purchased component requirements by time-phased order releases. In the literature on order review and release strategies, time- phased order releases are described as a worthy alternative to load limited release mechanisms. This paper initializes the development of a stochastic model that quantifies the consequences of time-phased order releases on the stochastic system behavior. This is done by introducing them in an open queueing network composed of two M/M/1 stations. The core of the analysis is focused on the modified flow variability which is specified by the second-order stationary departure process at the first station in the routing. It is a process characterized by a negligible autocorrelation. Based on the stationary-interval method and the asymptotic method, we propose an approximating renewal process for the modified departure process. The modelling efforts provide interesting conclusions and practical insights on some coordination issues in stochastic multi-echelon systems.

Differential evolution to solve the lot size problem.

An Advanced Resource Planning model is presented to support optimal lot size decisions for performance improvement of a production system in terms of either delivery time or setup related costs. Based on a queueing network, a model is developed for a mix of multiple products following their own specific sequence of operations on one or more resources, while taking into account various sources of uncertainty, both in demand as well as in production characteristics. In addition, the model includes the impact of parallel servers and different time schedules in a multi-period planning setting. The corrupting influence of variabilities from rework and breakdown is explicitly modeled. As a major result, the differential evolution algorithm is able to find the optimal lead time as a function of the lot size. In this way, we add a conclusion on the debate on the convexity between lot size and lead time in a complex production environment. We show that differential evolution outperforms a steepest descent method in the search for the global optimal lot size. For problems of realistic size, we propose appropriate control parameters for the differential evolution in order to make its search process more efficient.Production planning; Lot sizing; Queueing networks; Differential evolution;

Estimating process batch flow times in a two-stage stochastic flowshop with overlapping operations.

Processes; Time;

Coordination and synchronization of material flows in supply chains: an analytical approach.

The coordination of joint material flows is a key element in supply chain management. Although analytical models for the coordination of materials are of great practical value, literature analyzing them remains scarce. This article contributes to this gap by studying a generic supply chain model. The supply chain is assumed to have a single production facility that is supplied by two independent suppliers. The field of combinatorics serves as a means to derive exact results for important performance measures, and the results suggest insights related to several supply chain management principles.Assembly; Synchronization; Coordination; Supply chain; Combinatorics;

Clips: a capacity and lead time integrated procedure for scheduling.

We propose a general procedure to address real life job shop scheduling problems. The shop typically produces a variety of products, each with its own arrival stream, its own route through the shop and a given customer due date. The procedure first determines the manufacturing lot sizes for each product. The objective is to minimize the expected lead time and therefore we model the production environment as a queueing network. Given these lead times, release dates are set dynamically. This in turn creates a time window for every manufacturing order in which the various operations have to be sequenced. The sequencing logic is based on a Extended Shifting Bottleneck Procedure. These three major decisions are next incorporated into a four phase hierarchical operational implementation scheme. A small numerical example is used to illustrate the methodology. The final objective however is to develop a procedure that is useful for large, real life shops. We therefore report on a real life application.Model; Models; Applications; Product; Scheduling;