Aircraft rotable inventory optimisation: development of a new solution

Analysis of the use of ICT in the aerospace industry has prompted the detailed investigation of an inventory-planning problem. There is a special class of inventory, consisting of expensive repairable spares for use in support of aircraft operations. These items, called rotables, are not well served by conventional theory and systems for inventory management. The context of the problem, the aircraft maintenance industry sector, is described in order to convey some of its special characteristics in the context of operations management. A literature review is carried out to seek existing theory that can be applied to rotable inventory and to identify a potential gap into which newly developed theory could contribute. Current techniques for rotable planning are identified in industry and the literature: these methods are modelled and tested using inventory and operational data obtained in the field. In the expectation that current practice leaves much scope for improvement, several new models are proposed. These are developed and tested on the field data for comparison with current practice. The new models are revised following testing to give improved versions. The best model developed and tested here comprises a linear programming optimisation, which finds an optimal level of inventory for multiple test cases, reflecting changing operating conditions. The new model offers an inventory plan that is up to 40% less expensive than that determined by current practice, while maintaining required performance.

A new inventory model for aircraft spares

A special inventory problem is presented: aircraft spares that are repaired and returned to spares, called rotable inventory. Rotable inventory is not consumed so does not change in the medium term, but is rotated through operational, maintenance and stock phases. The objective for inventory performance is fleet Service Level (SL), which effects aircraft dispatch performance. A model is proposed where the fleet SL drives combined stock levels such that cost is optimized. By holding greater numbers of lower-cost items and holding lower levels of more expensive items, it is possible to achieve substantial cost savings while maintaining performance. This approach is shown to be an advance over the current literature and is tested with case data, with conclusive results.

Impaired executive functioning in subclinical compulsive checking with ecologically valid stimuli in a working memory task

We previously showed that working memory (WM) performance of subclinical checkers can be affected if they are presented with irrelevant but misleading information during the retention period (Harkin and Kessler, 2009, 2011). The present study differed from our previous research in the three crucial aspects. Firstly, we employed ecologically valid stimuli in form of electrical kitchen appliances on a kitchen countertop in order to address previous criticism of our research with letters in locations as these may not have tapped into the primary concerns of checkers. Secondly, we tested whether these ecological stimuli would allow us to employ a simpler (un-blocked) design while obtaining similarly robust results. Thirdly, in Experiment 2 we improved the measure of confidence as a metacognitive variable by using a quantitative scale (0–100), which indeed revealed more robust effects that were quantitatively related to accuracy of performance. The task in the present study was to memorize four appliances, including their states (on/off), and their locations on the kitchen countertop. Memory accuracy was tested for the states of appliances in Experiment 1, and for their locations in Experiment 2. Intermediate probes were identical in both experiments and were administered during retention on 66.7% of the trials with 50% resolvable and 50% irresolvable/misleading probes. Experiment 1 revealed the efficacy of the employed stimuli by revealing a general impairment of high- compared to low checkers, which confirmed the ecological validity of our stimuli. In Experiment 2 we observed the expected, more differentiated pattern: High checkers were not generally affected in their WM performance (i.e., no general capacity issue); instead they showed a particular impairment in the misleading distractor-probe condition. Also, high checkers’ confidence ratings were indicative of a general impairment in metacognitive functioning. We discuss how specific executive dysfunction and general metacognitive impairment may affect memory traces in the short- and in the long-term.

The role of working memory in compulsive checking and OCD:a systematic classification of 58 experimental findings

Despite the large body of research regarding the role of memory in OCD, the results are described as mixed at best (Hermans et al., 2008). For example, inconsistent findings have been reported with respect to basic capacity, intact verbal, and generally affected visuospatial memory. We suggest that this is due to the traditional pursuit of OCD memory impairment as one of the general capacity and/or domain specificity (visuospatial vs. verbal). In contrast, we conclude from our experiments (i.e., Harkin & Kessler, 2009, 2011; Harkin, Rutherford, & Kessler, 2011) and recent literature (e.g., Greisberg & McKay, 2003) that OCD memory impairment is secondary to executive dysfunction, and more specifically we identify three common factors (EBL: Executive-functioning efficiency, Binding complexity, and memory Load) that we generalize to 58 experimental findings from 46 OCD memory studies. As a result we explain otherwise inconsistent research – e.g., intact vs. deficient verbal memory – that are difficult to reconcile within a capacity or domain specific perspective. We conclude by discussing the relationship between our account and others', which in most cases is complementary rather than contradictory.

An evaluation of Landsat Thematoc Mapper (TM) and spot- HRV data, in grasslands inventory in the UK

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Fuzzy knowledge-based approach to treating uncertainty in inventory control

Inventory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

Decision support system for vendor managed inventory supply chain:a case study

Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).

Technological innovation in electronic inventory solutions:an analysis of patent data

The purpose of this paper is to investigate the technological development of electronic inventory solutions from perspective of patent analysis. We first applied the international patent classification to classify the top categories of data processing technologies and their corresponding top patenting countries. Then we identified the core technologies by the calculation of patent citation strength and standard deviation criterion for each patent. To eliminate those core innovations having no reference relationships with the other core patents, relevance strengths between core technologies were evaluated also. Our findings provide market intelligence not only for the research and development community, but for the decision making of advanced inventory solutions.

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations.