The Application of Material Requirements Planning (MRP) System to Aircraft Parts Inventory

As the title implies, the application of MRP into an aviation context is the response to the huge cost of parts holding in an ever-expanding industry. The nature of intermittent parts demand (unpredictable parts), typical of maintenance and overhaul inventory parts control, is investigated both to illustrate the deficiency of traditional ROP systems for dependent-demand inventory and other applications in the area of lot sizing and forecasting with a specific exploration into sources of demand lumpiness. In order to investigate current inventory procedure, we surveyed 175 airline operators and maintenance service organisations, to explore the status of MRP and ROP worldwide. This response showed current inventory practice to be less than effective and that better systems were required, leading us to investigate specific problems experienced namely; lot-size and forecasting methods used within the MRP concept. MRP had made some inroads into the aviation sector, but a number of factors have prevented its general uptake. Through a case study of KTM-uk’s workshop practices within overhaul and repair, we apply various solutions to lot-size and forecasting methodology in order to realise best practice, putting forward a small scale MRP-spreadsheet as a working tool. In the process we present two predictive models; a Lot-size Predictive Cost Model. LPCM, and a Predictive Error-Forecasting Model, PEFM. The models in their present form use seventeen lot-size and thirteen forecasting methods respectively, simplifying material management through appropriate estimates of costs and planning needs. Within lotsizing, we found that under almost all operations conditions the WWA and MSM2 methods give the best performance. Similarly the WMA method followed by the Holt and the Croston methods work best for forecasting intermittent demand parts

Demand Control Loops for a Global Spare Parts Management

Part VI: Services, Supply Chains and OperationsInternational audienceTimely, reliable supply of customers with spare parts is a key factor for business success in many branches. In the field of aviation the competition and cost pressures in the MRO sector (Maintenance, Repair and Overhaul) increased strongly in recent decades. Large maintenance organizations offer component pooling services for aircraft operators. A main challenge in the processes of MRO service providers is the calculation of the optimal stock level for pool components. The basis of an optimal inventory planning for the supply of spare parts is the quality of the demand input parameters used for the calculation. This paper describes the processes and the challenges of the MRO spare parts management as well as the approaches of a research project to face these challenges

Periodic control of intermittent demand items: theory and empiricial analysis

In this paper we propose a modification to the standard forecasting, periodic order-up-to-level inventory control approach to dealing with intermittent demand items, when the lead-time length is shorter than the average inter-demand interval. In particular, we develop an approach that relies upon the employment of separate estimates of the inter-demand intervals and demand sizes, when demand occurs, directly for stock control purposes rather than first estimating mean demand and then feeding the results in the stock control procedure. The empirical performance of our approach is assessed by means of analysis on a large demand data set from the Royal Air Force (RAF, UK). Our work allows insights to be gained on the interactions between forecasting and stock control as well as on demand categorization-related issues for forecasting and inventory management purposes

Identification of the requirements for a handheld computer in aviation maintenance

Identification of the requirements for a handheld computer in aviation maintenance by Goossen, Kuyper and de Boer. In many MRO departments problems are encountered with the use of manuals, task lists and ‘black books’ on paper. These problems are a critical factor for aviation safety and productivity in MRO. The NLR (Dutch National Aerospace Laboratory) has proposed a system called PAMELA using handheld computers to overcome many of the problems associated with the use of paper documents in aviation maintenance. The PAMELA concept has not previously been tested in actual practice. This paper presents the results of a study to determine which functions will need to be fulfilled by a handheld computer in aviation maintenance for it to be successfully introduced. Referentie Goossen, M., Kuyper, Y., & de Boer, R.J. (2011), Identification of the requirements for a handheld computer in aviation maintenance, 2nd Air Transport and Operations Symposium (ATOS 2011), Delft, The Netherlands

An integrative approach to inventory control

Inventory control systems consist of three types of methods: forecasting, safety stock sizing and order timing and sizing. These are all part of the interpretation of a planning environment to generate replenishment orders, and may consequently affect the performance of a system. It is therefore essential to integrate these aspects into a complete inventory control process, to be able to evaluate different methods for certain environments as well as for predicting the overall performance of a system. In this research a framework of an integrated inventory control process has been developed, covering all relations from planning environment to performance measures. Based on this framework a simulation model has been constructed; the objective is to show how integrated inventory control systems perform in comparison to theoretical predictions as well as to show the benefits of using an integrated inventory control process when evaluating the appropriateness of inventory control solutions. Results indicate that only simple applications (for instance without forecasts or seasonality) correspond to theoretical cost and service level calculations, while more complex models (forecasts and changing demand patterns) show the need for tight synchronization between forecasts and reordering methods. As the framework describes all relations that affect performance, it simplifies the construction of simulation models and makes them accurate. Another benefit of the framework is that it may be used to transfer simulation models to real-world applications, or vice versa, without loss of functionality