128 research outputs found
Forecasting intermittent demand
Methods for forecasting intermittent demand are compared using a large data-set from the UK Royal Air Force (RAF). Several important results are found. First, we show that the traditional per period forecast error measures are not appropriate for intermittent demand, even though they are consistently used in the literature. Second, by comparing target service levels to achieved service levels when inventory decisions are based on demand forecasts, we show that Croston's method (and a variant) and Bootstrapping clearly outperform Moving Average and Single Exponential Smoothing. Third, we show that the performance of Croston and Bootstrapping can be significantly improved by taking into account that each lead time starts with a demand
A comparison of inventory control policies for a joint manufacturing/Remanufacturing environment with remanufacturing yield loss
We consider a joint manufacturing / remanufacturing environment with remanufacturing yield loss. Demand and return follow independent stationary Poisson processes. Returns can be disposed off upon arrival to the system. Manufacturing and remanufacturing operations performed in the same facility at exponential rates. Yield information becomes available after remanufacturing. Demands that are not directly satisfied are lost. We investigate what inventories to consider when making production and disposal decisions, with the objective of maximizing the long-run average expected profit. Four different policies are compared that base disposal decisions on either the local (returns) inventory or the global inventory, and production decisions on either the local (serviceable) inventory or the global inventory. By modelling the system as a Markov process, expressions for the profit associated with each policy are derived. An extensive numerical study shows that it is always optimal to base disposal decisions on the local inventory and production decisions on the global inventory within the parameter sets considered. A sensitivity analysis reveals further insights.inventory control;product returns;remanufacturing;yield loss
Optimise initial spare parts inventories: an analysis and improvement of an electronic decision tool.
Control of spare parts is very difficult as demands can be very low (once in a few years is no exception), while the consequences of a stockout can be severe. While in the past many companies choose to have very large spares inventories, one now observe trends in areas with good transportation connections to keep spare parts at the suppliers. Hence it is very important to make a good selection of which spare parts to stock at the start-up of new plants. To this end Shell Global Solutions has developed an electronic decision tool, called E-SPIR. In this report we analyse the decision rules used in it. We consider stockout penalties and advise to use criticality classifications instead. Furthermore, we investigate minimum stock levels, demand distributions and order quantities.
A comparison of inventory control policies for a joint manufacturing/Remanufacturing environment with remanufacturing yield loss
We consider a joint manufacturing / remanufacturing environment with remanufacturing yield loss. Demand and return follow independent stationary Poisson processes. Returns can be disposed off upon arrival to the system. Manufacturing and remanufacturing operations performed in the same facility at exponential rates. Yield information becomes available after remanufacturing. Demands that are not directly satisfied are lost. We investigate what inventories to consider when making production and disposal decisions, with the objective of maximizing the long-run average expected profit. Four different policies are compared that base disposal decisions on either the local (returns) inventory or the global inventory, and production decisions on either the local (serviceable) inventory or the global inventory. By modelling the system as a Markov process, expressions for the profit associated with each policy are derived. An extensive numerical study shows that it is always optimal to base disposal decisions on the local inventory and production decisions on the global inventory within the parameter sets considered. A sensitivity analysis reveals further insights
Reverse logistics in a pharmaceutical company: a case study
Schering spends considerable effort to undertake product recovery activities in pharmaceutical production. The two main recovery activities are by-product recycling and solvent reuse. The main driver for engaging in these activities is economical. Recovery leads to annual savings of approximately DM 25 million, which is about 8.5 % of the total production cost. This figure does not include additional savings due to reduced
disposal quantities and additional costs due to investments in recovery equipment, of which we do not have reliable estimates. Furthermore, being engaged in recovery activities has additional benefits for Schering that are related to the reduced waste stream: production is in accordance with environmental legislation, the
company builds an environmentally friendly image, and there is less strain on the environment. The downside of the recovery activities is that they complicate production and inventory planning. Especially the added complexity of production planning, resulting from cycles in the production structure, is a disadvantage.A simple MRP approach, as commonly used in practice, is no longer applicable but has to be replaced by a
more sophisticated planning procedure. Schering has developed an advanced decision support system which integrates a MIP procedure. Thus it turns out that reverse logistics also is a field which creates challenges for developing advanced planning systems in order to support practical decision making
Optimise initial spare parts inventories: an analysis and improvement of an electronic decision tool.
Control of spare parts is very difficult as demands can be very low (once in a few years is no exception), while the consequences of a stockout can be severe. While in the past many companies choose to have very large spares inventories, one now observe trends in areas with good transportation connections to keep spare parts at the suppliers. Hence it is very important to make a good selection of which spare parts to stock at the start-up of new plants. To this end Shell Global Solutions has developed an electronic decision tool, called E-SPIR. In this report we analyse the decision rules used in it. We consider stockout penalties and advise to use criticality classifications instead. Furthermore, we investigate minimum stock levels, demand distributions and order quantities
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
Value of information analysis for assessing risks and benefits of nanotechnology innovation
Background
Decisions on adoption of technological innovation are difficult for manufacturers, especially for small and medium enterprises (SMEs) who have limited resources but often drive product development. Decision analytic methods have been applied to regulatory issues in the nanotechnology sector but such applications to market innovation are not found in the literature. Value of information (VoI) is a decision analytic method for quantifying the benefit of acquiring additional information to support such analyses that can be used to help in a wide range of manufacturing decisions.
Results
This paper develops a VoI methodology for comparative evaluation of technological alternatives and applies it to a real case study aimed at the selection between a coating system containing nano-TiO2 and alternative conventional paints. The aim of this approach is to aid SMEs and larger industries in deciding whether to further develop the nano-enabled product and in evaluating to which extent investing in more research about risks and/or benefits would be worthwhile.
Conclusions
Results demonstrated how prioritization in information gaining can improve riskâbenefit analyses and impact on both risk management and innovation decision making. By applying the proposed methodology, SMEs and larger industries might easily identify optimal data gathering and/or research strategies to formulate solid development and risk management plans
- âŠ