Diode area melting single-layer parametric analysis of 316L stainless steel powder

Diode area melting (DAM) is a novel additive manufacturing process that utilises customised architectural arrays of low power laser diode emitters for high speed parallel processing of metallic powdered feedstock. The laser diodes operate at shorter laser wavelengths (808 nm) than conventional SLM fibre lasers (1064 nm) theoretically enabling more efficient energy absorption for specific materials. This investigation presents a parametric analysis of the DAM process, identifying the effect of powder characteristics, laser beam profile, laser power and scan speed on the porosity of a single-layer sample. Also presented is the effect of process energy density on melt pool depth (irradiated thermal energy penetration capable of achieving melting) on 316L stainless steel powder. An analysis of the density and the melt depth fraction of single layers is presented in order to identify the conditions that lead to the fabrication of fully dense DAM parts. Energy densities in excess of 86 J/mm3 were theorised as sufficient to enable processing of fully dense layers

Future Logistics: What to Expect, How to Adapt

As a result of global societal and economic as well as technological developments logistics and supply chains face unprecedented challenges. Climate change, the need for more sustainable products and processes, major political changes, the advance of “Industry 4.0” and cyber-physical system are some of the challenges that require radical solutions, but also present major opportunities. The authors argue that logistics has to reinvent itself, not only to address these chal-lenges but also to cope with mass individualization on the one hand while exploit-ing broad-fielded business applications of artificial intelligence on the other hand. An essential challenge will be to find a compromise between these two develop-ments – in line and in combination with the known triple-bottom line for sustaina-bility – that will define supply chains and logistics concepts of the future

Supply chain management resources, capabilities and execution

This paper identifies inter- and intra-organisational management resources that determine the level of execution of inter-firm alliance supply chain management (SCM). By drawing on network and resource-based view theories, a conceptual model proposes the effects of SCM resources and capabilities as influencing factors on SCM execution. The model was tested using survey data from studies conducted in two European supply chain environments. Variance-based structural equation modelling confirmed the hypothesised hierarchical order of three proposed antecedents: internal SCM resources affect joint SCM resources, which in turn influence collaborative SCM-related processes and finally SCM execution. An importance-performance analysis for both settings shows that providing and investing in internal SCM resources should be a priority when aiming to increase SCM execution. The theoretical contribution of this paper lies in confirming that the improvement of SCM execution follows a clear pathway featuring internal supply chain resources as one of the main drivers. The practical implications of this research include the development of a prioritisation list of measures that elevate SCM execution in the two country settings

Optimal static pricing for a tree network

We study the static pricing problem for a network service provider in a loss system with a tree structure. In the network, multiple classes share a common inbound link and then have dedicated outbound links. The motivation is from a company that sells phone cards and needs to price calls to different destinations. We characterize the optimal static prices in order to maximize the steady-state revenue. We report new structural findings as well as alternative proofs for some known results. We compare the optimal static prices versus prices that are asymptotically optimal, and through a set of illustrative numerical examples we show that in certain cases the loss in revenue can be significant. Finally, we show that static prices obtained using the reduced load approximation of the blocking probabilities can be easily obtained and have near-optimal performance, which makes them more attractive for applications.Massachusetts Institute of Technology. Center for Digital BusinessUnited States. Office of Naval Research (Contract N00014-95-1-0232)United States. Office of Naval Research (Contract N00014-01-1-0146)National Science Foundation (U.S.) (Contract DMI-9732795)National Science Foundation (U.S.) (Contract DMI-0085683)National Science Foundation (U.S.) (Contract DMI-0245352

Business process management and supply chain collaboration: a critical comparison

The link between a firm and supply chain (SC) members has been recognised as one of the key issues for ensuring business success and achieving competitive advantage. Indeed, working across organisational boundaries is required to accomplish effective responses to customers’ needs. Our preliminary research confirmed that there are positive relationships between business process management (BPM), supply chain collaboration (SCC), collaborative advantage and organisational performance. This study is a step further and uses a multiple case design to illuminate the results and gain a greater understanding from extensive discussions about these relationships. By means of semi-structured interviews, the three main issues were identified as: (1) the link between BPM and organisational performance; (2) the link between BPM and SCC; and (3) the contextual factors and benefits achieved from working collaboratively with SC partners. The different scenarios of the link between BPM and SCC were developed in a taxonomy, and the case studies were used to illustrate the experience of intra- and inter-organisational practices in the developing economy of Thailand. The case studies’ results explain in depth that both BPM and SCC are important for improving organisational performance and competitiveness. BPM not only improves organisational performance directly, but also assists with collaborative activities that in turn help to improve internal capabilities. Additionally, the comparisons in issues relating to firm size, industry type, relationship closeness and relationship length were also included in this study

A single-vendor and a single-buyer integrated inventory model with ordering cost reduction dependent on lead time

Lead time is one of the major limits that affect planning at every stage of the supply chain system. In this paper, we study a continuous review inventory model. This paper investigates the ordering cost reductions are dependent on lead time. This study addressed two-echelon supply chain problem consisting of a single vendor and a single buyer. The main contribution of this study is that the integrated total cost of the single vendor and the single buyer integrated system is analyzed by adopting two different (linear and logarithmic) types ordering cost reductions act dependent on lead time. In both cases, we develop effective solution procedures for finding the optimal solution and then illustrative numerical examples are given to illustrate the results. The solution procedure is to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries from the single vendor and the single buyer in one production run, so that the integrated total cost incurred has the minimum value. Ordering cost reduction is the main aspect of the proposed model. A numerical example is given to validate the model. Numerical example solved by using Matlab software. The mathematical model is solved analytically by minimizing the integrated total cost. Furthermore, the sensitivity analysis is included and the numerical examples are given to illustrate the results. The results obtained in this paper are illustrated with the help of numerical examples. The sensitivity of the proposed model has been checked with respect to the various major parameters of the system. Results reveal that the proposed integrated inventory model is more applicable for the supply chain manufacturing system. For each case, an algorithm procedure of finding the optimal solution is developed. Finally, the graphical representation is presented to illustrate the proposed model and also include the computer flowchart in each model

Enabling sustainable energy futures: Factors influencing green supply chain collaboration

In order to explore the relationship between sustainability strategies and future energy needs and demands (hence energy futures), supply chains (SCs) need to continue to reduce their CO2 emissions through developing their green credentials and improving overall performance; noting that the assimilation of such environmental aspects into production, SCs and logistics are considered as complex processes. Knowledge management (KM) has long been seen as an enabler to support intensive collaboration efforts – on which green initiatives are largely based. The supply chain management (SCM) and KM areas have largely focused on improving organisational performance. While the latter research has yielded successful outcomes in many different sectors, there is still a scarcity of research studies focusing on identifying influential factors that highlight those aspects which may enable green supply chain collaboration (GrSCC) to occur, thus leading to sustainable energy futures and carbon-efficient production. To increase inter-organisational synchronisation, organisations often call for SC partners to implement common business processes and sources of knowledge. This paper therefore aims to contribute to the research domain by examining the role of KM in facilitating GrSCC. Through the identification of key factors extrapolated from the normative literature, a model for implementing GrSCC using a futures-based perspective is proposed. This paper inductively demonstrates the relationship between identified GrSCC factors through the application of a fuzzy cognitive mapping (FCM) technique. Findings from this research support a futures-based perspective that enhances understanding and refines forward-looking strategies for GrSCC. Through the exploration of two GrSCC scenarios using the given technique, this paper reports a granular perspective of positive and negative causal factors that support enabling energy futures that enhance green supply credentials

Cost-based filtering for stochastic inventory control

Abstract. An interesting class of production/inventory control problems considers a single product and a single stocking location, given a stochastic demand with a known non-stationary probability distribution. Under a widely-used control policy for this type of inventory system, the objective is to find the optimal number of replenishments, their timings and their respective order-up-to-levels that meet customer demands to a required service level. We extend a known CP approach for this problem using a cost-based filtering method. Our algorithm can solve to optimality instances of realistic size much more efficiently than previous approaches, often with no search effort at all.