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PurposeThe customer order decoupling point (CODP) concept addresses the issue of customer engagement in the manufacturing process. This has traditionally been applied to material flows, but has more recently been applied to engineering activities. This later subject becomes of particular importance to companies operating in "engineer-to-order" (ETO) supply chains, where each order is potentially unique. Existing conceptualisations of ETO are too generic for practical purposes, so there is a need to better understand order penetration in the context of engineering activities, especially design. Hence, the purpose of this paper is to address the question "how do customer penetration concepts apply to engineering design activities?"Design/methodology/approachA collaborative form of inquiry is adopted, whereby academics and practitioners co-operated to develop a conceptual framework. Within this overarching research design, a focus group of senior practitioners and multiple case studies principally from complex civil and structural engineering as well as scientific equipment projects are used to explore the framework.FindingsThe framework results in a classification of nine potential engineering subclasses, and insight is given into order penetration points, major uncertainties and enablers via the case studies. Focus group findings indicate that different managerial approaches are needed across subclasses.Practical implicationsThe findings give insight for companies that engage directly with customers on a one-to-one basis, outlining the extent of customer penetration in engineering activities, associated operational strategies and choices regarding the co-creation of products with customers. Care should be taken in generalising beyond the sectors addressed in the study.Originality/valueThe paper refines the definition of the ETO concept, and gives a more complete understanding of customer penetration concepts. It provides a comprehensive reconceptualization of the ETO category, supported by exploratory empirical research.

WMC Ltd is a medium‐sized company which manufactures and distributes mechanical/ electrical equipment for the construction industry. Constitutes a case study which illustrates the re‐engineering methodology developed for WMC in order to improve its material and logistics control strategies. The first re‐engineering approach initiated by WMC was to make wholesale changes affecting internal operations in order to achieve world‐class performance. Finds that optimization of the manufacturing operations highlighted further problems caused by an inefficient inventory control system. Hence, the updated objective became that of designing an improved material and logistics control strategy to ensure that the right materials are in the right place in the right quantity at the right time. Provides, therefore, an interesting case study example of how WMC achieved effective supply‐chain management through the development of a three‐stage re‐engineering framework encompassing changes to the internal structure, inventory control structure and supplier management strategies. The results are applicable to many other market sectors.

PurposeThe purpose of this paper is to refine a logistics triad uncertainty model taking a supply chain perspective, to determine and assess the different causes and sources of supply chain uncertainty that impact on the sustainability of the UK road freight transport sector.Design/methodology/approachTo clarify the link between sustainability and transport uncertainty, a methodological triangulation strategy is applied combining the results of eight focus groups and an online structured questionnaire.FindingsThe findings indicate that the main drivers impacting the sustainability of transport operations are delays, variable demand/poor information, delivery constraints and insufficient supply chain integration. The consequence of these problems is to reduce the efficiency of transport operations.Research limitations/implicationsThe model has been refined based only on participants' perceptions. Therefore, the finding should also be verified through the investigation of real‐world situations. Moreover, the transport uncertainty model needs to be incorporated within a wider business process re‐engineering approach to evaluate solutions to reduce transport uncertainty within supply chains.Practical implicationsThe findings further strengthen the understanding of the main uncertainty sources within supply chains in the UK. The internal root causes of uncertainty can be mitigated while external issues have to be accommodated; therefore, mitigation techniques, methods and strategies for reducing external and internal supply chain uncertainty in transport operations need to be identified through the research.Originality/valueThis paper determines the industry perceived economic and environmental risks associated with transport operations in four UK sectors.

PurposeFlexibility is a fundamental performance objective for manufacturing operations, allowing them to respond to changing requirements in uncertain and competitive global markets. Additive manufacturing machines are often described as "flexible," but there is no detailed understanding of such flexibility in an operations management context. The purpose of this paper is to examine flexibility from a manufacturing systems perspective, demonstrating the different competencies that can be achieved and the factors that can inhibit these in commercial practice.Design/methodology/approachThis study extends existing flexibility theory in the context of an industrial additive manufacturing system through an investigation of 12 case studies, covering a range of sectors, product volumes, and technologies. Drawing upon multiple sources, this research takes a manufacturing systems perspective that recognizes the multitude of different resources that, together with individual industrial additive manufacturing machines, contribute to the satisfaction of demand.FindingsThe results show that the manufacturing system can achieve seven distinct internal flexibility competencies. This ability was shown to enable six out of seven external flexibility capabilities identified in the literature. Through a categorical assessment the extent to which each competency can be achieved is identified, supported by a detailed explanation of the enablers and inhibitors of flexibility for industrial additive manufacturing systems.Originality/valueAdditive manufacturing is widely expected to make an important contribution to future manufacturing, yet relevant management research is scant and the flexibility term is often ambiguously used. This research contributes the first detailed examination of flexibility for industrial additive manufacturing systems.

PurposeMuch of the recent research on supply chain uncertainty has focused on relationships between manufacturers and suppliers and existing models have therefore been based on this dyadic structure. The aim is to establish a supply chain uncertainty model that explicitly incorporates transport operations and hence the logistics triad; supplier, customer and transport carrier.Design/methodology/approachThis is a literature‐based activity that synthesises and extends existing models of supply chain uncertainty.FindingsThe paper develops a new model to reflect the nature of transport operations. Consequently, it identifies five main categories of uncertainty, namely from the points of view of the supplier, the customer and the carrier, respectively, the control systems used in the supply chain and external factors. The interfaces between the uncertainty categories involving all three parties of the logistics triad are identified, so as to develop a more holistic perspective on supply chain uncertainty and how it can be reduced.Research limitations/implicationsThis paper is conceptual in nature and empirical research into the area of transport uncertainty will be required to validate its findings. Following this, the model can be used to investigate and evaluate improvements in the economic and/or environmental performance of freight transport within supply chains.Practical implicationsThe model is intended to provide a framework within which organisations, including logistics providers, can develop a supply chain strategy to mitigate the effects of uncertainty. By categorising uncertainty into the types described, organisations may determine where the greatest uncertainties lie and hence develop a prioritised plan for supply chain re‐engineering by initially targeting those uncertainties with the most significant implications for supply chain efficiency.Originality/valueLittle research has been undertaken on the impact of uncertainties on transport in the context of collaborative supply chain management. The model rationalises uncertainties into various types taking into account the nature of the logistics triad.