A survey of simulation techniques in commerce and defence

Despite the developments in Modelling and Simulation (M&S) tools and techniques over the past years, there has been a gap in the M&S research and practice in healthcare on developing a toolkit to assist the modellers and simulation practitioners with selecting an appropriate set of techniques. This study is a preliminary step towards this goal. This paper presents some results from a systematic literature survey on applications of M&S in the commerce and defence domains that could inspire some improvements in the healthcare. Interim results show that in the commercial sector Discrete-Event Simulation (DES) has been the most widely used technique with System Dynamics (SD) in second place. However in the defence sector, SD has gained relatively more attention. SD has been found quite useful for qualitative and soft factors analysis. From both the surveys it becomes clear that there is a growing trend towards using hybrid M&S approaches

Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Cooperative Longevity and Sustainable Development in a Family Farming System

This paper focuses on small holding, family farming in Southeast Spain where agricultural economic activity is predominantly organized around cooperative business models. A variety of diverse studies on the Almería agricultural and credit cooperative sector and the exploration of social-economic and eco-social indicators, in addition to economic-market indicators are presented. Each correspond to a cooperative “logic” that spans theoretical perspectives from the dominant economic-market model, new institutionalism, and an eco-social approach, echoing theories on collective coordination governance, and the avoidance of the “tragedy of the commons”. The latter is of particular importance given environmental challenges and scarce resources for agricultural activity. The cooperatives in Almería have increasingly relied on collective collaboration and coordination in order to meet social-economic and social-ecological challenges, transforming their role from that founded on a market dominant logic to that of cooperation as a coordination mechanism based on the mutual benefit of the community and environment. In turn, their ability to meet a wide range of needs and challenges of members and the community leads to their longevity. Cooperatives are able to act as both a market and non-market coordination mechanism, balancing the economic, social, and environmental dimensions, such that neither market nor non-market logics are dominant or exclusive

SME Information Sourcing for Innovation and Export Market Development: From Local or External Networks?

A survey analysis of innovation information and input sourcing of New South Wales regional exporting firms indicates that the majority of regional exporters were small to medium sized enterprises (SMEs). The analysis shows that these SMEs have been able to establish their own extensive information linkages into the international economy. Consequently, the need to assess and develop the benefits of linkages between small and large firms is not highly significant within the New South Wales regions. The analysis indicates that international networking by SMEs brings knowledge to the regions, which facilitates intra-firm learning. However, it suggests that SME’s local or regional linkages are relatively underdeveloped, as a source of new knowledge for innovation activity. This is in contrast to the main body of economic literature, which argues that small regional exporters utilize local networks as a major input into their success. This research identifies intensification in the usage of regional networks as one means of improving SME performance in more remote regions. The analysis also indicates that a two-way effect results by the diversity of regional SME export sector base. Firstly, it restricts the client-supplier relationships preventing closer industry specific collaborations but secondly, it can be advantageous in that it restricts competition between regional exporters. This creates conditions allowing some information sharing regarding the opportunities and ways of entering overseas markets, which do not affect the competitive position of the mentoring firm. In concluding, the paper argues that the basic requirements for regional learning development are in place but requires an increase in the interaction intensity between local SMEs in order to achieve a higher level of collaboration and knowledge sharing.New South Wales, SMEs, small and medium enterprises, regional development, innovation, international networking

An integrated model for green partner selection and supply chain construction

Stricter governmental regulations and rising public awareness of environmental issues are pressurising firms to make their supply chains greener. Partner selection is a critical activity in constructing a green supply chain because the environmental performance of the whole supply chain is significantly affected by all its constituents. The paper presents a model for green partner selection and supply chain construction by combining analytic network process (ANP) and multi-objective programming (MOP) methodologies. The model offers a new way of solving the green partner selection and supply chain construction problem both effectively and efficiently as it enables decision-makers to simultaneously minimize the negative environmental impact of the supply chain whilst maximizing its business performance. The paper also develops an additional decision-making tool in the form of the environmental difference, the business difference and the eco-efficiency ratio which quantify the trade-offs between environmental and business performance. The applicability and practicability of the model is demonstrated in an illustration of its use in the Chinese electrical appliance and equipment manufacturing industry