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

Forecasting Intermittent Demand by Hyperbolic-Exponential Smoothing

Croston's method is generally viewed as superior to exponential smoothing when demand is intermittent, but it has the drawbacks of bias and an inability to deal with obsolescence, in which an item's demand ceases altogether. Several variants have been reported, some of which are unbiased on certain types of demand, but only one recent variant addresses the problem of obsolescence. We describe a new hybrid of Croston's method and Bayesian inference called Hyperbolic-Exponential Smoothing, which is unbiased on non-intermittent and stochastic intermittent demand, decays hyperbolically when obsolescence occurs and performs well in experiments.Comment: Earlier versions of this work were presented at the 25th European Conference on Operations Research, 2012; and at the 54th Annual Conference of the UK Operational Research Society, 2012. A journal version is in preparatio

A forecasting decision on the sales volume of printers in Taiwan: An exploitation of the analytic network process

[[abstract]]This study applies the Analytic Network Process (ANP) to forecast the sales volume of printers in Taiwan for adjusting the recycling and treatment fee as an incentive for recycling industries. When historical data are lacking and when a broad spectrum of social impact is involved, the ANP, with the capacity to manage dependence and feedback among the factors, can serve as a tool to forecast outcomes by using expert judgment. The priorities derived from numerical judgment are similar to probabilities. They are obtained from the limit supermatrix of the ANP that represents forecasts for the next period. The result of back testing has shown that the ANP’s percentage error is small compared with those of some naïve statistical techniques. Sensitivity analysis is also made to ensure robustness of the model. Finally, the characteristic strengths of the Analytic Hierarchy Process (AHP) and ANP in forecasting are discussed to simplify their use in future applications.[[incitationindex]]SCI[[incitationindex]]EI[[booktype]]紙

On Double-Boundary Non-Crossing Probability for a Class of Compound Processes with Applications

We develop an efficient method for computing the probability that a non-decreasing, pure jump (compound) stochastic process stays between arbitrary upper and lower boundaries (i.e., deterministic functions, possibly discontinuous) within a finite time period. The compound process is composed of a process modelling the arrivals of certain events (e.g., demands for a product in inventory systems, customers in queuing, or claims/capital gains in insurance/dual risk models), and a sequence of independent and identically distributed random variables modelling the sizes of the events. The events arrival process is assumed to belong to the wide class of point processes with conditional stationary independent increments which includes (non-)homogeneous Poisson, binomial, negative binomial, mixed Poisson and doubly stochastic Poisson (i.e., Cox) processes as special cases. The proposed method is based on expressing the non-exit probability through Chapman-Kolmogorov equations, re-expressing them in terms of a circular convolution of two vectors which is then computed applying fast Fourier transform (FFT). We further demonstrate that our FFT-based method is computationally efficient and can be successfully applied in the context of inventory management (to determine an optimal replenishment policy), ruin theory (to evaluate ruin probabilities and related quantities) and double-barrier option pricing or simply computing non-exit probabilities for Brownian motion with general boundaries

Implementing reliability, availability, maintainability and supportability RAMS for the MRO industry: A case study at European Airlines

Aerospace Engineerin

The application of material requirements planning (MRP) system to aircraft parts inventory

Available from British Library Document Supply Centre- DSC:DXN060194 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

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

A seven-factor procedural analysis of safety culture Known measurement - a case study at KLM E&M

Aerospace Management and Operations DepartmentAerospace Engineerin