On two-echelon inventory systems with Poisson demand and lost sales

We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u

Continuous maintenance and the future – Foundations and technological challenges

High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle ‘big data’ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security

Study on Customer Demand Forecasting Models, Stock Management, Classification and Policies for Automobile Parts Manufacturing Company N.A.C.C. (An Advance on Classical Models)

The primary intent of the current research is to provide insights regarding the management of spare parts within the supply chain, in conjunction with offering some methods for enhancing forecasting and inventory management. In particular, to use classical forecasting methods, the use of weak and unstable demand is not recommended. Furthermore, statistical performance measures are not involved in this particular context. Furthermore, it is expected that maintenance contracts will be aligned with different levels. In addition to the examination of some literature reviews, some tools will guide us through this process. The article proposes new performance analysis methods that will help integrate inventory management and statistical performance while considering decision maker priorities through the use of different methodologies and parts age segmentation. The study will also identify critical level policies by comparing different types of spenders according to the inventory management model, also with separate and common inventory policies. Each process of the study is combined with a comparative analysis of different forecasting methods and inventory management models based on N.A.C.C. parts supply chain data, allowing us to identify a set of methodologies and parameter recommendations based on parts segmentation and supply chain prioritization

Last time buy and repair decisions for spare parts

Original Equipment Manufacturers (OEM’s) of advanced capital goods often offer service contracts for system support to their customers, for which spare parts are needed. Due to technological changes, suppliers of spare parts may stop production at some point in time. As a reaction to that decision, an OEM may place a so-called Last Time Buy (LTB) order to cover demand for spare parts during the remaining service period, which may last for many years. The fact that there might be other alternative sources of supply in the next periods\ud complicates the decision on the LTB. In this paper, we develop a heuristic method to find the near- optimal LTB quantity in presence of an imperfect repair option of the failed parts that can be returned from the field. Comparison of our method to simulation shows high approximation accuracy. Numerical experiments reveal that repair is an excellent option as\ud alternative sourcing, even if it is more expensive than buying a new part, because of postponement of the repair decisions. In addition, we show the impact of other key parameters on costs and LTB quantity

Integrated Systems Health Management as an Enabler for Condition Based Maintenance and Autonomic Logistics

Health monitoring systems have demonstrated the ability to detect potential failures in components and predict how long until a critical failure is likely to occur. Implementing these systems on fielded structures, aircraft, or other vehicles is often a struggle to prove cost savings or operational improvements beyond improved safety. A system architecture to identify how the health monitoring systems are integrated into fielded aircraft is developed to assess cost, operations, maintenance, and logistics trade-spaces. The efficiency of a health monitoring system is examined for impacts to the operation of a squadron of cargo aircraft revealing sensitivity to and tolerance for false alarms as a key factor in total system performance. The research focuses on the impacts of system-wide changes to several key metrics: materiel availability, materiel reliability, ownership cost, and mean downtime. Changes to theses system-wide variables include: diagnostic and prognostic error, false alarm sensitivity, supply methods and timing, maintenance manning, and maintenance repair window. Potential cost savings in maintenance and logistics processes are identified as well as increases in operational availability. The result of this research is the development of a tool to conduct trade-space analyses on the effects of health monitoring techniques on system performance and operations and maintenance costs

Maintenance spare parts planning and control : a framework for control and agenda for future research

This paper presents a framework for planning and control of the spare parts supply chain in organizations that use and maintain high-value capital assets. Decisions in the framework are decomposed hierarchically and interfaces are described. We provide relevant literature to aid decision making and identify open research topics. The framework can be used to increase the e??ciency, consistency and sustainability of decisions on how to plan and control a spare parts supply chain. Applicability of the framework in di??erent environments is investigated