Customising with 3D printing: The role of intelligent control

© 2018 Elsevier B.V. The emergence of direct digital manufacturing creates new opportunities for the production of highly customised goods especially when it is combined with conventional manufacturing methods. Nevertheless, this combination creates a need for systems that can effectively manage and control the resulting distributed manufacturing process. In this paper, we explore three different configurations that can enable direct digital manufacturing for customisation, ranging from fully integrated to inter-organisational set up. Additionally, control requirements of such systems are developed and the suitability of intelligent control is explored. By ‘intelligent control’ we mean production control that is capable of assessing and interacting with the production environment and adapting production accordingly. We argue that the so called intelligent product paradigm provides a suitable mechanism for the development of such intelligent control systems. In this approach, the intelligent product directly co-ordinates with design agent, 3D printing agents and other conventional manufacturing system agents to schedule, assign and execute tasks independently. Via a case example of a realistic production system, we propose and implement such an intelligent control system and we analyse its feasibility in supporting 3D printing enabled customisation

Information Systems for Managing Second Order Dynamics of Organizations

From the point of view of information technology the past decade can be designated the “decade of ERP”. A global movement of implementing integrated systems for optimising the fulfilment of orders has dominated both investments from large and medium corporations and the focus of research and educational institutions. The results of these implementations sometimes have been dramatic: Significant improvements of throughput time, and at the same time clear decreases in inventory. Organisations have become like machines. Interesting material - though not in all aspects consistent - on the improvement of productivity is collected in (Potthof, 1998). Unfortunately, and strangely enough, only little research has been done in the consequences of ERP systems on the flexibility and adaptability of organisations

The responsive reply chain: the influence of the positioning of decoupling points

Manufacturing supply chains have been challenged by high competition, dynamic, and stochastic conditions. They have to be constantly responsive in today’s ever-changing manufacturing environment. The proper positioning of decoupling points for material flow and information flow has a significant potential for increasing responsiveness in a supply chain. Positioning the material decoupling point as close to the end consumer as possible whilst the information decoupling point is positioned upstream is the key to the industries’ ability to reduce lead time and enhance performance in the dynamic behaviour of the supply chain. [Continues.

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

The feasibility of adopting clothing mass customisation in South Africa

Abstract: Mass Customisation (MC) is increasingly seen as a strategy to survive in the competitive clothing fashion markets. This importance to retail sales necessitates its consideration in the South African context. There is a paucity of literature on adopting MC so exploring the feasibility of MC for South African clothing manufacturers was a step in understanding what is required from manufacturers. Three corporate clothing manufacturers were selected for qualitative interviews to determine whether they currently exhibit identified competencies from literature considered essential to undertake MC. Two manufacturers exhibited key competencies of communication, human capital, flexibility and technology needed for MC success

From physical marketing to web marketing

Reviews the criticism of the 4P marketing mix framework as the basis of traditional and virtual marketing planning. Argues that the customary marketing management approach, based on the popular marketing mix 4Ps paradigm, is inadequate in the case of virtual marketing. Identifies two main limitations of the marketing mix when applied in online environments namely the role of the Ps in a virtual commercial setting and the lack of any strategic elements in the model. Identifies the critical factors of the Web marketing and argues that the basis for successful e-commerce is the full integration of virtual activities into the company's physical strategy, marketing plan and organisational processes. The 4S elements of the Web marketing mix framework offer the basis for developing and commercialising business to consumer online projects. The model was originally developed for educational purposes and has been tested and refined by means of three case studies