Preventive maintenance and the interval availability distribution of an unreliable production system

Traditionally, the optimal preventive maintenance interval for an unreliable production system has been determined by maximizing its limiting availability. Nowadays, it is widely recognized that this performance measure does not always provide relevant information for practical purposes. This is particularly true for order-driven manufacturing systems, in which due date performance has become a more important, and even a competitive factor. Under these circumstances, the so-called interval availability distribution is often seen as a more appropriate performance measure. Surprisingly enough, the relation between preventive maintenance and interval availability has received little attention in the existing literature. In this article, a series of mathematical models and optimization techniques is presented, with which the optimal preventive maintenance interval can be determined from an interval availability point of view, rather than from a limiting availability perspective. Computational results for a class of representative test problems indicate that significant improvements of up to 30% in the guaranteed interval availability can be obtained, by increasing preventive maintenance frequencies somewhere between 10 and 70%

Integral optimization of spare parts inventories in systems with redundancies

In this paper, we analyze spare parts supply for a system with a "k-out-of-N" redundancy structure for key components, different standby policies (cold, warm and hot standby redundancy) and local spare parts inventories for sub-components. We assume multiple part types (sub-components) that fail randomly with exponentially distributed interfailure times. Due to the standby policies and the limited number of installed components, the total failure rate depends on the state of the system. Replacement times and stock replenishment times are also assumed to be exponentially distributed and depend on the part types. We present an exact method together with a simple and effi�cient approximation scheme for the evaluation of the system availability given certain stock levels. The proposed approximation is further used in a simple optimization heuristic to demonstrate how the total system costs can be reduced if the redundancy structure is optimized while taking into account the local stock of the spare parts. The presented numerical results clearly show the importance of the local inventories with spares even in the systems with redundancies

Dynamic transport scheduling under multiple resource constraints

This paper presents a heuristic for the dynamic vehicle scheduling problem with multiple resource capacity constraints. In the envisaged application, an automated transport system using Automated Guided Vehicles, bottleneck resources are (1) vehicles, (2) docks for loading/unloading, (3) vehicle parking places, and (4) load storage space. This problem is hard, because interrelated activities (loading, transportation, unloading) at several geographical locations have to be scheduled under multiple resource constraints, where the bottleneck resource varies over time. Besides, the method should be suitable for real-time planning. We developed a dedicated serial scheduling method and analyzed its dynamic behavior using discrete event simulation. We found that our method is very well able to find good vehicle schedules satisfying all resource constraints. For comparison, we used a simple approach where we left out the resource constraints and extended the processing times by statistically estimated waiting times to account for finite capacities. We found that our newly designed method finds better schedules in terms of service levels

Interaction between intelligent agent strategies for real-time transportation planning

In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to different collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents offer jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead strategies instead of a myopic strategy (10–20%) and (ii) the joint effect of two look-ahead strategies is larger than the effect of an individual strategy. To provide an indication of the savings that might be realized under centralized decision making, we benchmark our results against an integer programming approach

The selective use of emergency shipments for service-contract differentiation

Suppliers of capital goods increasingly offer performance-based service contracts with customer-specific service levels. We use selective emergency shipments of spare parts to differentiate logistic performance: We apply emergency shipments in out-of-stock situations for combinations of parts and customer classes that yield service levels close to the class-specific targets. We develop two heuristics to solve this problem. An extensive numerical experiment reveals average cost savings of 4.4% compared to the one-size-fits-all approach that is often used in practice. It is best to combine our policy with critical levels, which yields an average cost saving of 13.9%

Determinación de hexosamines en orina por HPLC para el diagnóstico de mucopolisacariosis tipo III

Treballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2014, Tutors: Dra. Elisabet Fuguet Jordà i Dr. Rafael Artuch IriberriIn the present work a reported analytical method was optimized in order to improve the diagnostic of a rare disease: Mucopolysaccharidoses type III (MPS III). This process is based on the separation and quantification of hexosamines (glucosamine and galactosamine), released as products of glycosaminoglycans (GAGs) hydrolysis presents in urine, by HPLC and detected by fluorescence measures. The concentration of galactosamine and glucosamine in urine of 20 persons as control sample and 9 patients with MPS III was determined. The control group showed similar concentrations of both hexosamines in urine, whereas in the group of MPS III patients the concentration of glucosamine was significantly higher than galactosamine. According to the obtained data, it was demonstrated that the ratio of concentrations galactosamine/glucosamine is the most useful parameter to discern people affected by MPS III, being a normal ratio 0.91±0.08 and 0.28±0.03 the ratio to diagnose the disease. It was established a unique reference interval to control sample for every considered biochemical parameter. According to the procedure, GAGs were hydrolyzed with HCl and the released hexosamines were derivatized with anthranilic acid. Finally, different products were separated and quantified by reverse phase HPLC and with fluorescence detector