Integrated Environmental Process Planning for the Design & Manufacture of Automotive Components

Advanced Product Quality Planning (APQP) logic is widely used by manufacturers for the design and manufacture of automotive components. Manufacturers are increasingly finding difficulties to incorporate environmental considerations in the broad range of products that they manufacture. Therefore, there is a need for a systematic method for environmental process planning to evaluate product configurations and their associated environmental impact. The framework and models discussed in this paper can deal with a variety of product characteristics and environmental impacts through a selection of Environmental Performance Indicators (EPIs) for a final product configuration. The framework and models have been applied in a real-life application and have proven that changes in product design or process selection can reduce the product's environmental impact and increase process efficiency. Hence, manufacturers can use the framework and models during the Advanced Product Quality Planning (APQP) process to benchmark each product variation that they manufacture in a standardised manner and realise cost saving opportunities

Multi-product, multi-level product control system analysis

Several techniques are applicable to the modelling of production and inventory control systems. In this thesis discrete linear control theory is examined as a method of modelling multi-product, multi-level systems. These systems are categorised and a general discrete linear control model is used to determine system stability and to predict system responses to specific patterns of input information. The response of the system to random variability in input or other system variable is also shown to be predictable. A library of sub-system models is provided and the method is illustrated by examples and a case study. Alternative modelling techniques rely upon sequential simulation, either directly or in solving equations representing the system. The need to include forecasting, inventory and production decision-making procedures makes such models large and their sequential nature imposes the need for complete remodelling for each system modification and for each input pattern. Where random effects are modelled, protracted runs are necessary to achieve statistically acceptable results. In contrast, discrete linear control theory provides a nonsequential model, thereby alleviating these problems. Thus it is possible both to reduce computing expense and increase the range of systems susceptible to manual analysis. The method is limited by the restriction of linearity, but, in many practical situations this restriction poses no insuperable difficulty in the interpretation of results

Multi-product, multi-level product control system analysis

Several techniques are applicable to the modelling of production and inventory control systems. In this thesis discrete linear control theory is examined as a method of modelling multi-product, multi-level systems. These systems are categorised and a general discrete linear control model is used to determine system stability and to predict system responses to specific patterns of input information. The response of the system to random variability in input or other system variable is also shown to be predictable. A library of sub-system models is provided and the method is illustrated by examples and a case study. Alternative modelling techniques rely upon sequential simulation, either directly or in solving equations representing the system. The need to include forecasting, inventory and production decision-making procedures makes such models large and their sequential nature imposes the need for complete remodelling for each system modification and for each input pattern. Where random effects are modelled, protracted runs are necessary to achieve statistically acceptable results. In contrast, discrete linear control theory provides a nonsequential model, thereby alleviating these problems. Thus it is possible both to reduce computing expense and increase the range of systems susceptible to manual analysis. The method is limited by the restriction of linearity, but, in many practical situations this restriction poses no insuperable difficulty in the interpretation of results

The current status of process planning for multi-material rapid prototyping fabrication

doi:10.4028/www.scientific.net/AMR.118-120.625 The current status of process planning for multi-material rapid prototyping fabricatio

Interpretive structural modelling of risk sources in a virtual organisation

International audienceSpeedier network decision making together with shorter time to bring items to market together with lower network operating costs all result from enhanced knowledge sharing. In addition re-use of enterprise and network knowledge resulting from improved capture means that any risk of repeating earlier project work is limited, repetition of past mistakes is reduced. Decisions are made with greater awareness of any risks involved and therefore there is likely to be a reduction in costs arising from faulty decisions and failed collaborations. While there are many advantages attaching to the use of virtual organizations (VOs) there are also challenges, including risks that have become apparent through undertaking a review of the literature. In total 13 sources of risk were found stemming from the network related risks in a VO, where the emphasis of the study was placed,. This paper contains a thorough study that will identify these threats as well as gaining a sound understanding of them by examining them one by one as they have been identified by the literature and previous studies. Subsequently, their relative importance will be analysed through the use of Structural Modeling (ISM) using information gathered in a questionnaire

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

An ontology supported risk assessment approach for the intelligent configuration of supply networks

As progress towards globalisation continues, organisations seek ever better ways with which to configure and reconfigure their global production networks so as to better understand and be able to deal with risk. Such networks are complex arrangements of different organisations from potentially diverse and divergent domains and geographical locations. Moreover, greater focus is being put upon global production network systems and how these can be better coordinated, controlled and assessed for risk, so that they are flexible and competitive advantage can be gained from them within the market place. This paper puts forward a reference ontology to support risk assessment for product-service systems applied to the domain of global production networks. The aim behind this is to help accelerate the development of information systems by way of developing a common foundation to improve interoperability and the seamless exchange of information between systems and organisations. A formal common logic based approach has been used to develop the reference ontology, utilising end user information and knowledge from three separate industrial domains. Results are presented which illustrate the ability of the approach, together with areas for further work

Towards the definition of a Science Base for Enterprise Interoperability: A European Perspective

Research on Enterprise Interoperability (EI) has evolved to meet real pragmatic needs to support the ever more collaborative nature of, for example, enterprise supply chains, and virtual enterprises. Research outputs have therefore focused on generating solutions to current problems, rather than to developing a body of knowledge which is structured for ease of re-use. In Europe there is move to define just such a structure: an Enterprise Interoperability Science Base (EISB). We explore here the current state of this ongoing research, reviewing the understanding gained so far, and looking to the likely future outcomes. However this is clearly not just a European research domain. The main purpose of presenting the European perspective is to stimulate interaction with researchers in all regions who have an interest in the domain. We therefore address three issues. We review the development of neighbouring sciences, identifying science base structures, and methodologies for their development. The definition and objectives of a science base are analysed, leading to an outline structure for an EISB to include formalised problem and solution spaces as well as structured EI domain knowledge. Twelve Scientific Themes of EI are identified and the current state of research in each is briefly discussed