Remco Germs

Workload balancing capability of pull systems in MTO production

Pull systems focusing on throughput time control and applicable in situations with high variety and customisation are scarce. This paper compares three unit-based pull systems that can cope with such situations: POLCA, CONWIP and m-CONWIP. These systems control the shop floor throughput time of orders by limiting the number of orders on the shop floor. However, their effectiveness in terms of reducing total throughput time is questioned. Theory states that an improvement in the average total throughput time will be due to the workload balancing capability of a pull system, but that many pull systems lack this capability. This paper shows that this workload balancing capability exists for POLCA and m-CONWIP, but not for CONWIP. The magnitude of the effect differs strongly, depending on the configuration of the system, the order arrival pattern and the variability of the processing time of the orders.

Lower tolerance-based Branch and Bound algorithms for the ATSP

In this paper, we develop a new tolerance-based Branch and Bound algorithm for solving NP-hard problems. In particular, we consider the asymmetric traveling salesman problem (ATSP), an NP-hard problem with large practical relevance. The main algorithmic contribution is our lower bounding strategy that uses the expected costs of including arcs in the solution to the assignment problem relaxation of the ATSP, the so-called lower tolerance values. The computation of the lower bound requires the calculation of a large set of lower tolerances. We apply and adapt a finding from 23] that makes it possible to compute all lower tolerance values efficiently. Computational results show that our Branch and Bound algorithm exhibits very good performance in comparison with state-of-the-art algorithms, in particular for difficult clustered ATSP instances.

Analysis of finite-buffer state-dependent bulk queues

In this paper, we consider a general state-dependent finite-buffer bulk queue in which the rates and batch sizes of arrivals and services are allowed to depend on the number of customers in queue and service batch sizes. Such queueing systems have rich applications in manufacturing, service operations, computer and telecommunication systems. Interesting examples include batch oven processes in the aircraft and semiconductor industry; serving of passengers by elevators, shuttle buses, and ferries; and congestion control mechanisms to regulate transmission rates in packet-switched communication networks. We develop a unifying method to study the performance of this general class of finite-buffer state-dependent bulk queueing systems. For this purpose, we use semi-regenerative analysis to develop a numerically stable method for calculating the limiting probability distribution of the queue length process. Based on the limiting probabilities, we present various performance measures for evaluating admission control and batch service policies, such as the loss probability for an arriving group of customers and for individual customers within a group. We demonstrate our method by means of numerical examples.

Placement of Effective Work-In-Progress Limits in Route-Specific Unit-Based Pull Systems.

Unit-based pull systems control the throughput time of orders in a production system by limiting the number of orders on the shop floor. In production systems where orders can follow different routings on the shop floor, route-specific pull systems that control the progress of orders on the shop floor by placing limits on the number of orders in (parts of) a routing, have shown to be effective in controlling throughput times. This is because route-specific pull systems are able to create a balanced distribution of the amount of work on the shop floor, which leads to shorter and more reliable throughput times. The placement of limits on work-in-progress in a route-specific pull system determines to a large extent the workload balancing capability of such a system. This paper shows how the placement of work-in-progress limits affects the workload balancing capability and thereby the throughput time performance of a route-specific unit-based pull system, namely POLCA.

Loss probabilities for the mx/gy/1/k+b bulk queue

In this article we analyze the MX/GY/1/K+B bulk queue. For this model, we consider three rejection policies: partial acceptance, complete rejection, and complete acceptance. For each of these policies, we are interested in the loss probability for an arriving group of customers and for individual customers within a group. To obtain these loss probabilities, we derive a numerically stable method to compute the limiting probabilities of the queue length process under all three rejection policies. At the end of the article we demonstrate our method by means of a numerical example.

Order acceptance and scheduling policies for a make-to-order environment with family-dependent lead and batch setup times

In many make-to-order production situations with batch setup times, customer orders are grouped into family-dependent batches to limit the loss of capacity due to setups. These batches, however, cannot be too large, since the make-to-order character requires that orders have to be produced in time. This trade-off between setup time efficiency and due-date adherence creates a challenging scheduling problem referred to in the literature as the Customised Stochastic Lot Scheduling Problem. Typically, suppliers reduce the complexity of the production problem by quoting lead times that are equal for all customer families. This choice, however, is in many cases too restrictive. In this paper, we show quantitatively by means of Markov decision processes (MDPs) that using family-dependent lead times can result in a significant gain in profit as compared with using standard lead times. We develop a simple heuristic acceptance/scheduling policy, and demonstrate that this heuristic performs very well compared with the optimal policy of the MDP for a wide range of parameters.