Iain Stalker

Small and Medium-sized Enterprises (SMEs) face steep challenges in fulfilling sustainability and resilience requirements when joining global supply chains. These challenges often relate to lack of capabilities, accreditations and/or capacity demanded by OEMs and Tier 1 players in the process of forming a supply chain composition. To address some of the challenges and lower entry barriers for SMEs, this paper formalises a Collaboration Design Method (CDM) that can assemble and coordinate supplier teams responding to a tender from a large buyer. CDM comprises five recursive design decisions: (1) Decomposing tendering goals; (2) Assigning sub-goals to suppliers in a team; (3) Operationalizing sub-goals through supplier processes within a team; (4) Decomposing processes to identify steps that can be outsourced; and (5) Defining coordination mechanisms. Feedback from industrial SMEs indicates that CDM provides a viable approach to tame supply chain formation complexity and ease barriers that prevent SMEs from collaborating in global supply chains.

Demand shocks and fluctuations underscore the need for new approaches to coordinate collaboration between firms to scale up production. This paper proposes an approach to formalise product and process requirements via a collaboration ontology and applies semantic reasoning techniques for process formation. Our approach contributes to production research by providing flexibility in coordinating firms engaged in demand-driven collaboration. The proposed approach has four core dimensions: (1) The Collaboration ontology builds on a set of product assembly requirements, process steps, their input/output resources and semantic rules; (2) the ontology reasoner derives resource dependencies between the steps; (3) the java tool interprets resource dependencies as possible transitions in Business Process Management Notation (BPMN); (4) a workflow engine exe-cutes the generated product assembly process. The approach and the ontology were validated in an industrial aerospace tendering scenario demonstrating its practical relevance for firms seeking demand-driven collaborations to react to production changes. Finally, we position and explain our contributions to the body of knowledge in collaborative production engineering.

Forming collaborative assembly along supply chains is a challenge in the presence of resource limitations. This paper presents an Ontology-driven Assembly Design Method (OADM) to facilitate the design of demand-driven SME collaborations envisioned in digital transformation initiatives such as Industry 4.0. The Relevance cycle addresses the key requirement to reducing coordination costs of such SME collaborations. The Design cycle develops the ontology, which includes: (i) goals, supplier processes, and resources as hierarchies of classes; (ii) properties to interconnect these classes; and (iii) SWRL rules to derive a possible combination of process steps to reach the goal of collaborative assembly. The feedback from SME Cluster managers indicates that OADM is a promising approach to overcoming barriers to planning demand-driven SME collaborations. The Rigor cycle explains its contribution to collaborative industrial engineering.

To successfully rise to the challenges of contemporary physical and social contexts, and thus secure a more sustainable world, (process) engineering (under)graduates must learn to engage effectively with other professionals. This demands that we structure learning opportunities that make explicit with whom engineers need to engage and promote softer skills that form an essential foundation of effective professional engineering practice. As a step towards this, we present a workspace that provides a holistic perspective on the intersections of the various value chains that obtain in manufacturing and process industries; this framework helps to identify key partners from professions and stakeholder groups. We also show how this framework informs the discussion around employability and professional competence.

Our interest here lies in supporting important, but routine and time-consuming activities that underpin success in highly distributed, collaborative design and manufacturing environments; and how information structuring can facilitate this. To that end, we present a simple, yet powerful approach to team formation, partner selection, scheduling and communication that employs a different approach to the task of matching candidates to opportunities or partners to requirements (matchmaking): traditionally, this is approached using either an idea of 'nearness' or 'best fit' (metric-based paradigms); or by finding a subtree within a tree (data structure) (tree traversal). Instead, we prefer concept lattices to establish notions of 'inclusion' or 'membership': essentially, a topological paradigm. While our approach is substantive, it can be used alongside traditional approaches and in this way one could harness the strengths of multiple paradigms.

An Extended enterprise (EE) is a comprehensive conceptual framework that facilitates firms' working synergistically. Through the Industry 4.0 framework, large orders from retailers can equitably be distributed (assigned) to small and medium-sized enterprises (SMEs). This paper reports research on modelling and simulation processes for distributing (allotting) apparel orders to a cluster of SMEs in an extended enterprise framework. The distribution processes discussed in this study are mainly on allocating, sharing or dividing order quantities among collaborating business entities within an EE framework. The study employed Arena software as one of the discrete-event simulation software packages to illustrate the distribution processes of order quantities, particularly when many retailers request apparel quantities from many manufacturers. Through an EE framework, firms can gain competitive advantages by strengthening their supply chain partnerships. Several activities need to be controlled and monitored by any virtual factory scheduler service, which distributes and optimises bulk orders amongst manufacturers.