Optimization of PCB component placements for the collect-and-place machines

This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.

Spatial aspects of MRSA epidemiology:A case study using stochastic simulation, kernel estimation and SaTScan

The identification of disease clusters in space or space-time is of vital importance for public health policy and action. In the case of methicillin-resistant Staphylococcus aureus (MRSA), it is particularly important to distinguish between community and health care-associated infections, and to identify reservoirs of infection. 832 cases of MRSA in the West Midlands (UK) were tested for clustering and evidence of community transmission, after being geo-located to the centroids of UK unit postcodes (postal areas roughly equivalent to Zip+4 zip code areas). An age-stratified analysis was also carried out at the coarser spatial resolution of UK Census Output Areas. Stochastic simulation and kernel density estimation were combined to identify significant local clusters of MRSA (p<0.025), which were supported by SaTScan spatial and spatio-temporal scan. In order to investigate local sampling effort, a spatial 'random labelling' approach was used, with MRSA as cases and MSSA (methicillin-sensitive S. aureus) as controls. Heavy sampling in general was a response to MRSA outbreaks, which in turn appeared to be associated with medical care environments. The significance of clusters identified by kernel estimation was independently supported by information on the locations and client groups of nursing homes, and by preliminary molecular typing of isolates. In the absence of occupational/ lifestyle data on patients, the assumption was made that an individual's location and consequent risk is adequately represented by their residential postcode. The problems of this assumption are discussed, with recommendations for future data collection.

Governing inter-organisational R&D supplier collaborations:a study at Jaguar Land Rover

This article discusses the importance of collaboration with suppliers and partners during research and development (R&D) technology projects. It details how this can be accomplished using the collaborative enterprise governance (CEG) concept to manage a technology project. CEG is based on the premise that parts of companies work with parts of other companies, which are reconfigured on dynamic bases according to a variety of different internal and external factors. This article presents an overview of the founding literature, the CEG and its methodology, and examples based at Jaguar Land Rover in the UK. CEG has been used here to explain why some technology projects have succeeded while others have done less well. This article concludes by offering new propositions, inducted through grounded theory, relating to the successful management of R&D projects, which should be picked up by future research studies in the area.

Rethinking policy options for industry:Appropriateness of policies for industry and UK farming and food

Purpose - Studies the implementation of lean supply and partnership relationships in the UK food and farming industry to assess if these types of interventions are effective. Design/methodology/approach - Reviews the challenges affecting the UK supply chain for red meat. Describes the initiatives that were set up to develop a lean supply chain management approach and examines their application in the UK pig and beef industries. Assesses if these changes benefited all participants in the supply chains. Uses semi-structured interviews with key actors in each stage of the supply chain to do this, identifying the power relations within the supply chains and how these affected the outcomes for those participating in the chain. Findings - Concludes that lean initiatives were appropriate for the pig industry but were of limited value for the beef industry. Even within the pig industry, highlights that benefits were not shared equally, with producers, in particular, losing out. Lastly, points out that lean supply chain management is unlikely to be appropriate operationally and commercially in all circumstances in one industry. Argues for a differentiated policy approach and sets out a framework which enables decision makers to select industrial policy options. Research limitations/ implications - Describes the analysis and the framework developed from it. Originality/value - Assesses the effectiveness of lean supply chain management.