A development of logistics management models for the Space Transportation System

A new analytic queueing approach was described which relates stockage levels, repair level decisions, and the project network schedule of prelaunch operations directly to the probability distribution of the space transportation system launch delay. Finite source population and limited repair capability were additional factors included in this logistics management model developed specifically for STS maintenance requirements. Data presently available to support logistics decisions were based on a comparability study of heavy aircraft components. A two-phase program is recommended by which NASA would implement an integrated data collection system, assemble logistics data from previous STS flights, revise extant logistics planning and resource requirement parameters using Bayes-Lin techniques, and adjust for uncertainty surrounding logistics systems performance parameters. The implementation of these recommendations can be expected to deliver more cost-effective logistics support

Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems

This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.spare parts;reverse logistics;phase-out;PUSH-PULL repair;non stationary;Last Time Buy;business case

Power-by-the-hour: the role of technology in reshaping business strategy at Rolls-Royce

There is a recognised trend of manufacturing companies offering not only products, but services and even complete solutions to business problems. Research has highlighted economic, market demand and competitiveness factors as responsible for the re-shaping of business strategies that this has involved. This study analyses the extent to which another factor, technology, has been a significant factor in the switch from product oriented to service oriented strategies. A case study of the aero engine manufacturer Rolls-Royce is used to analyse the impact of technology, which is found to have led manufacturers to re-shape their business strategies. The study finds that developments in one technology in particular, namely digital electronics, have been a powerful enabling factor facilitating the implementation of service strategies. This provided original equipment manufacturers (OEMs) like Rolls-Royce with a competitive advantage relative to conventional service providers, by enabling them to acquire new knowledge management capabilities

Identifying, Tracking, and Prioritizing Parts Unavailability

The Air Force is pursuing several efficiency initiatives designed to reduce support function costs. One such initiative is an effort to reduce the flow days of items being repaired in the Air Force\u27s organic depots. Many end items are affected by awaiting parts (AWP) delays, which increase total flow days. The first step in reducing AWP delays is to identify which piece parts are causing the delays. A gap analysis was conducted to identify a process for creating a list of piece parts that are causing AWP delays. In addition, a clinimetric method was used to develop an aggregate measure of AWP impact by which the list of piece parts could be prioritized. The gap analysis showed that such a list can be created with Cognos, a reporting tool currently used by the depots, which can pull data from multiple information systems. In addition, only minor changes to information recorded throughout the repair process are needed. An aggregate measure of AWP impact was also created and tested. It produced significantly different prioritizations from the individual constituent variables, and provides a possible method for helping depot managers to understand decision tradeoffs between different parts shortage priorities

Scheduling policies for a repair shop problem

In this paper, we analyze a repair shop serving several fleets of machines that fail from time to time. To reduce downtime costs, a continuous-review spare machine inventory is kept for each fleet. A spare machine, if available on stock, is installed instantaneously in place of a broken machine. When a repaired machine is returned from the repair shop, it is placed in inventory for future use if the fleet has the required number of machines operating. Since the repair shop is shared by different fleets, choosing which type of broken machine to repair is crucial to minimize downtime and holding costs. The optimal policy of this problem is difficult to characterize, and, therefore, is only formulated as a Markov Decision Process to numerically compute the optimal cost and base-stock level for each spare machine inventory. As an alternative, we propose the dynamic Myopic(R) policy, which is easy to implement, yielding costs very close to the optimal. Most of the time it outperforms the static first-come-first-served, and preemptive-resume priority policies. Additionally, via our numerical study, we demonstrate that repair shop pooling is better than reserving a repair shop for each fleet

Framework for Evaluation of Strategies for Pooling of Repairable Spare Parts

Background: The ability to quickly provide parts for the supply of advanced technical systems in equipment-intensive industries (such as airlines and nuclear power plants) is critical to the systems overall performance. In order to maintain a targeted system availability large quantities of spare parts are often required which in turn results in excessive inventory costs. Seeing as inventory systems often account for a large proportion of a business‟ costs a tough issue faced by companies in these industries is how to reduce the total inventory cost without having a negative impact on the system availability. An approach that may successfully deal with such a problem is pooling. Pooling refers to an arrangement in which multiple owners of the same type of technical systems cooperate by sharing their inventories. Purpose: The theoretical purpose of the thesis is to emphasize different pooling strategies and to identify and assess the characteristics of the strategies. The practical purpose of the thesis is to develop a robust method that facilitates a fair comparison of considered strategies. The objective is thus to develop a generic model that evaluates soft values (here, referred to as soft aspects) for each strategy, and also, to put the soft aspects in relation to the annual cost of a strategy in a final model. iv Methodology: The initial phase of the thesis was dedicated to a desk study review of current literature within the field of study. Recently published scientific articles, papers authored by consultants at Systecon, and literature used in courses at the Faculty of Engineering at Lund University lay the basis for the theoretical framework. The framework developed is derived from discussions with the supervisors in connection with interviews carried out with; relevant Systecon customers and company representatives at two trade fairs, Offshore Wind 2009 and Nordic Rail 2009. Conclusion: This thesis presents a framework for evaluation of strategies (stand alone, ad hoc cooperation, cooperative pooling, and commercial pooling) for pooling of repairable spare parts. Characteristics of all strategies are emphasized and assessed. From the characteristics, which are provided in Table 5.3, a model to evaluate soft values of each strategy is derived. The model, named evaluation of soft values, is provided in Table 5.4 and Table 5.5. Also, a methodical approach to derive a final strategy is provided in section 5.7. To make sure that a decision-maker is well aware of how the model should be applied, a fictitious case study is build up in where every step of the decision making process is thoroughly described. Furthermore, in the case study a final model that facilitates the derivation of a best strategy is presented. By means of a specified weighting coefficient and properly chosen set of scales, the final model provides with a final strategy. The outcome of the final model is based on the outcomes of the cost models and the outcomes of the evaluation of soft values model

Advanced Planning and Scheduling in the United States Air Force Depot-Level Maintenance

In the post cold war environment, the rapid deployment of combat capability is critical. Deployment lift capability is limited, however, so the real-time selection of the optimal combat asset mix that balances capability provided and sustainment required has become paramount. In this model, the value of a force mix is determined by the sum of the individual weapon system suitabilities against their assigned missions. The value is constrained by the numerical limits on the items required to create and support the force mix, and the lift required to move these items. The research considered heuristic and complete enumeration methods against the problem structure to develop a decision support model that expedites the selection of the best overall force mix. War planners are provided a decision support tool that objectively compares alternative force mix packages and selects the optimal asset mix in a reasonable amount of time while explicitly considering logistics constraints. This demonstrates the feasibility of an approach that integrates intelligence, operations, and logistics issues into a single decision support and planning tool for force mix decisions

A "DESIGN FOR AVAILABILITY" METHODOLOGY FOR SYSTEMS DESIGN AND SUPPORT

Prognostics and Health Management (PHM) methods are incorporated into systems for the purpose of avoiding unanticipated failures that can impact system safety, result in additional life cycle cost, and/or adversely affect the availability of a system. Availability is the probability that a system will be able to function when called upon to do so. Availability depends on the system's reliability (how often it fails) and its maintainability (how efficiently and frequently it is pro-actively maintained, and how quickly it can be repaired and restored to operation when it does fail). Availability is directly impacted by the success of PHM. Increasingly, customers of critical systems are entering into "availability contracts" in which the customer either buys the availability of the system (rather than actually purchasing the system itself) or the amount that the system developer/manufacturer is paid is a function of the availability achieved by the customer. Predicting availability based on known or predicted system reliability, operational parameters, logistics, etc., is relatively straightforward and can be accomplished using several methods and many existing tools. Unfortunately in these approaches availability is an output of the analysis. The prediction of system's parameters (i.e., reliability, operational parameters, and/or logistics management) to meet an availability requirement is difficult and cannot be generally done using today's existing methods. While determining the availability that results from a set of events is straightforward, determining the events that result in a desired availability is not. This dissertation presents a "design for availability" methodology that starts with an availability requirement and uses it to predict the required design, logistics and operations parameters. The method is general and can be applied when the inputs to the problem are uncertain (even the availability requirement can be represented as a probability distribution). The method has been demonstrated on several examples with and without PHM

Issue resolution at a large aerospace manufacturer

Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 39-40).UTC Aerospace Systems has a wide variety of problem solving tools driven by their Achieving Competitive Excellence (ACE) program. One tool that is frequently used to resolve and capture customer escapes is the 8D methodology. It is an eight-step process designed to identify, correct, and eliminate recurring problems and is useful in providing a feedback mechanism between the customers and suppliers. Its goal is to establish a permanent corrective action and focuses on the origin of the problem by determining its root causes. The objective of the project is to fully understand the cost benefit of implementing the 8D methodology. The initial investigation of the 8D process uncovered that some defects recorded using the 8D tool are omitted in metrics reporting, leading to poor issue resolution and limited feedback between customers and suppliers. Because the tool requires additional steps that were not required in previous problem solving techniques at UTC Aerospace Systems, it is both more cost and time intensive. To avoid wasteful spending, it is therefore important that the tool be applied only when necessary. A study was performed to identify situations when the 8D tool is used improperly. Two situations were identified: (1) when an 8D investigation is performed unnecessarily and (2) when the 8D investigation is not performed in a situation when it should be. In the first situation, the unnecessary implementation of the 8D tool results in wasted effort within the organization. In the second situation, the missed opportunity to implement the tool has the potential to allow future occurrences of the same defect that may have otherwise been avoided. Preventing a defect from occurring in the future is often achieved by redesigning a part to eliminate a systemic issue. It is therefore important to use the 8D tool in order to identify systemic issues more quickly and thereby reduce future repair costs. The costs associated with these two situations are further quantified in the project.by Sarah Clarke.M.B.A.S.M