A process framework for selecting supply system architecture in manufacturing supply chains and networks

The process framework comprises three phases, as follows: scope the supply chain/network; identify the options for supply system architecture and select supply system architecture. It facilitates a structured approach that analyses the supply chain/network contextual characteristics, in order to ensure alignment with the appropriate supply system architecture. The process framework was derived from comprehensive literature review and archival case study analysis. The review led to the classification of supply system architectures according to their orientation, whether integrated; partially integrated; co-ordinated or independent. The classification was combined with the characteristics that influence the selection of supply system architecture to encapsulate the conceptual framework. It builds upon existing frameworks and methodologies by focusing on structured procedure; supporting project management; facilitating participation and clarifying point of entry. The process framework was initially tested in three case study applications from the food, automobile and hand tool industries. A variety of industrial settings was chosen to illustrate transferability. The case study applications indicate that the process framework is a valid approach to the problem; however, further testing is required. In particular, the use of group support system technologies to support the process and the steps involving the participation of software vendors need further testing. However, the process framework can be followed due to the clarity of its presentation. It considers the issue of timing by including alternative decision-making techniques, dependent on the constraints. It is useful for ensuring a sound business case is developed, with supporting documentation and analysis that identifies the strategic and functional requirements of supply system architecture

Information system for road infrastructure booking

Booking of road infrastructure is a tool for management of ,,stresses´´ between traffic demand and available infrastructure capacity (supply). In this course entitlement to use of certain network elements (lane, zone, and parking lot) can be purchased. It can be applied at those network elements where traffic jams are generated regularly and travel time is unpredictable. Charges for use of infrastructure are proportional to the number of bookings. Its extent influences both travel mode and vehicle choice. ,,Intervention´´ in traffic flows is wanted, therefore its analysis and control require the use of knowledge in the following fields: transport network planning, traffic technology and transport informatics; in a system- and process-oriented approach. Model of this complex transport system has been built up; the operations are influenced by dynamic information

A network maturity mapping tool for demand-driven supply chain management : a case for the public healthcare sector

CITATION: Bvuchete, M., Grobbelaar, S. S. & Van Eeden, J. 2021. A network maturity mapping tool for demand-driven supply chain management : a case for the public healthcare sector. Sustainability, 13(21):11988, doi:10.3390/su132111988.The original publication is available at https://www.mdpi.comPublication of this article was funded by the Stellenbosch University Open Access FundThe healthcare supply chain is a complex adaptive ecosystem that facilitates the delivery of health products to the end patient in a cost-effective way. However, low forecast accuracy and high demand volatility in healthcare supply chains have resulted in an increase in stockouts, operational inefficiencies, poor health outcomes, and a significant increase in supply chain costs. To cope with these challenges, organisations are trying to adopt demand-driven supply chain management (DDSCM) operating practices which have been established in other sectors such as the telecommunications, fruit, and flower industries. However, previous studies have not considered these practices in the healthcare industry, and hence no methodologies exist that support the implementation of these practices in this context. Moreover, current studies present cases where the focus has been on improving and expanding individual organisational performance, but no supply chain network-level studies exist on the healthcare industry. Therefore, this paper provides a network-level analysis when addressing DDSCM in the healthcare industry. A grounded theory-based approach coupled with a conceptual framework analysis process was used to leverage a systematized literature review methodology with the development of a network maturity mapping tool for DDSCM which was validated in the public healthcare sector.https://www.mdpi.com/2071-1050/13/21/11988Publisher's versio

A decision support framework for sustainable supply chain management

Sustainable Supply Chain Management has become a topic of increased importance within the research domain. There is a greater need than ever before for companies to be able to assess and make informed decisions about their sustainability in the Supply Chains. There is a proliferation of research about its understanding and how to implement it in practice. This is mainly since sustainability has been assessed from various disciplines, organizational industries and organizational functional silos . There is a lack of comprehension, unified definition and appropriate implementation of Sustainable Supply Chain Management (SSCM), leading to failure in decision making for sustainability implementation within supply chains. The proposed research identifies the research gaps through the novel application of Systematic Literature Network Analysis (SLNA) to SSCM literature. In doing so, methods including Systematic Literature Review (SLR), Citation Network Analysis (CNA) and Citation Network Mapping of literature have been used to identify definitions, KPIs, barriers and drivers of SSCM from the literature. Furthermore, a combination of methods from Text Mining and Content Analysis has been used to identify KPIs, barriers and drivers from sustainability reports of top global manufacturing companies, to better understand the practices of organizations for SSCM. The consolidation of the findings from literature and practice led to the development of an SSCM Performance Evaluation Framework built on multiple methods. A 4-level hierarchical model has been developed by classifying the identified KPIs into Economic, Environment and Social as well as considering the key decision areas including tactical, strategic and operational. Furthermore, a rigorous data collection process was conducted among supply chain and sustainability managers from top global manufacturing firms and leading academicians in the field, assessing the identified SSCM KPIs. The collected data were analyzed through novel application of hybrid Multi-Criteria Decision Analysis (MCDA) methods, which includes Values Focused Thinking (VFT), Fuzzy Analytical Hierarchical Process (FAHP), Fuzzy Technique of Order Preference by Similarity to Ideal Solution (FTOPSIS) and Total Interpretive Structural Modelling (TISM), for prioritizing and modelling of interdependencies, interactions and weightages among SSCM KPIs. The results obtained were subsequently used to develop a Decision Support System (DSS) that allows managers to evaluate their sustainability by identifying problem areas and yielding guidance on the KPIS and most important areas to focus on for SSCM implementation. The application of DSS has been demonstrated in the context of a case company. From a theoretical development point of view, a Tree perspective framework contributing to the ecological Theory of Sustainability has been proposed through the identification of the most influential organizational theories, and how they interrelate with each other. Overall, the proposed research provides a holistic perspective of SSCM that incorporates the various aspects of organizations, relevant organizational theories and perspectives of academics and practitioners together. The proposed DSS may act as a guiding tool for managers and practitioners for SSCM implementation in companies

A roadmap to successful commercialization of autologous CAR T-cell products with centralized and bedside manufacture

The availability of two CAR T-cell therapies on the market has cemented the therapeutic potential of these products to treat oncology patients. However, in order for CAR T-cell therapies to be available to a wide number of patients, cell therapy developers must carefully design their manufacturing and commercialisation strategy. This analysis must take into account multiple factors related to the target market characteristics (EU v USA), the product features (e.g. dose size), manufacturing process (e.g. automated v manual platforms) as well as facility network (e.g. centralised v bedside manufacture) and supply chain requirements (e.g. fresh v frozen products). This presentation aims at assessing the implications of the choices made for each of these critical factors to provide a clear framework for decision-making during early stages of the development process of autologous CAR T-cell products. The resulting roadmap enables the successful commercialisation of these powerful therapeutics. This analysis was carried out using an advanced decisional tool developed at University College London. The case study assesses the economic and operational effects of the decisions made at the different levels of manufacturing and commercialisation strategy by computing metrics such as cost of goods, fixed capital investment, net present value, personnel requirement and facility footprint, while considering potential constraints relating to technology capacity, viral vector stock availability, product shelf life, market access and reimbursement strategies. Cost of goods (COG), net present value, process economics, supply chain, reimbursement, centralised, decentralised, bedside, GMP-in-a-box, market acces

Development of GIS based contamination risk assessment in water distribution systems

The study aims at developing a GIS based contamination Risk Assessment procedure in water distribution systems. Water distribution network analysis model EPANET 2.0 was integrated with ArcGIS 8.3 for the water quality analysis retrieving data from the GIS database. Water supply system of Zone VIII of Guntur, India was selected for the case study. The results of water quality simulation were displayed in the GIS interface and the areas affected were mapped with the spatial analyst tool of GIS. Data on number of household connections and standpipes affected by a particular event of contamination was also retrieved from the GIS database. The events resulting in high risk were identified from the GIS maps. This information helps in the decision making process of prioritizing the maintenance activities particularly, in case of limited fund availability. Since the resource availability for maintenance activities are limited in developing countries, prioritizing the activities using GIS helps to achieve maximum risk reduction

Including leakage in network models: an application to calibrate leak valves in EPANET

EPANET is one of the most widely used software packages for water network hydraulic modelling, and is especially interesting for educational and research purposes because it is in the public domain. However, EPANET simulations are demand-driven, and the program does not include a specific functionality to model water leakage, which is pressure-driven. Consequently, users are required to deal with this drawback by themselves. As a general solution for this problem, this paper presents a methodology for including leakage in EPANET models by following a two-stage process. Firstly, leakage is spatially distributed among the nodes, according to the characteristics of the network. Secondly, leakage is modelled through an emitter at each node. The process is described in detail and two numerical examples illustrate the applicability and advantages of the method. In addition, free access through a URL is provided to the leakage modelling tool that has been developed.Cobacho Jordán, R.; Arregui De La Cruz, F.; Soriano Olivares, J.; Cabrera Rochera, E. (2015). Including leakage in network models: an application to calibrate leak valves in EPANET. Journal of Water Supply: Research and Technology - Aqua. 64(2):130-138. doi:10.2166/aqua.2014.197S130138642Al-Ghamdi, A. S. (2011). Leakage–pressure relationship and leakage detection in intermittent water distribution systems. Journal of Water Supply: Research and Technology-Aqua, 60(3), 178-183. doi:10.2166/aqua.2011.003Almandoz, J., Cabrera, E., Arregui, F., Cabrera, E., & Cobacho, R. (2005). Leakage Assessment through Water Distribution Network Simulation. Journal of Water Resources Planning and Management, 131(6), 458-466. doi:10.1061/(asce)0733-9496(2005)131:6(458)Ameyaw, E. E., Memon, F. A., & Bicik, J. (2013). Improving equity in intermittent water supply systems. Journal of Water Supply: Research and Technology-Aqua, 62(8), 552-562. doi:10.2166/aqua.2013.065Boulos, P. F., & Bros, C. M. (2010). Assessing the carbon footprint of water supply and distribution systems. Journal - American Water Works Association, 102(11), 47-54. doi:10.1002/j.1551-8833.2010.tb11338.xCabrera, E., Pardo, M. A., Cobacho, R., & Cabrera, E. (2010). Energy Audit of Water Networks. Journal of Water Resources Planning and Management, 136(6), 669-677. doi:10.1061/(asce)wr.1943-5452.0000077Cabrera, E., Cobacho, R., Estruch, V., & Aznar, J. (2011). Analytical hierarchical process (AHP) as a decision support tool in water resources management. Journal of Water Supply: Research and Technology-Aqua, 60(6), 343-351. doi:10.2166/aqua.2011.016Cassa, A. M., & van Zyl, J. E. (2013). Predicting the head-leakage slope of cracks in pipes subject to elastic deformations. Journal of Water Supply: Research and Technology-Aqua, 62(4), 214-223. doi:10.2166/aqua.2013.094Cavallo, A., Di Nardo, A., De Maria, G., & Di Natale, M. (2013). Automated fuzzy decision and control system for reservoir management. Journal of Water Supply: Research and Technology-Aqua, 62(4), 189-204. doi:10.2166/aqua.2013.046Colombo, A. F., & Karney, B. W. (2002). Energy and Costs of Leaky Pipes: Toward Comprehensive Picture. Journal of Water Resources Planning and Management, 128(6), 441-450. doi:10.1061/(asce)0733-9496(2002)128:6(441)Prats, A. G., Picó, S. G., Alzamora, F. M., & Bello, M. Á. J. (2012). Random Scenarios Generation with Minimum Energy Consumption Model for Sectoring Optimization in Pressurized Irrigation Networks Using a Simulated Annealing Approach. Journal of Irrigation and Drainage Engineering, 138(7), 613-624. doi:10.1061/(asce)ir.1943-4774.0000452Germanopoulos, G. (1985). A technical note on the inclusion of pressure dependent demand and leakage terms in water supply network models. Civil Engineering Systems, 2(3), 171-179. doi:10.1080/02630258508970401GERMANOPOULOS, G., & JOWITT, P. (1989). LEAKAGE REDUCTION BY EXCESS PRESSURE MINIMIZATION IN A WATER SUPPLY NETWORK. Proceedings of the Institution of Civil Engineers, 87(2), 195-214. doi:10.1680/iicep.1989.2003Giustolisi, O., Savic, D., & Kapelan, Z. (2008). Pressure-Driven Demand and Leakage Simulation for Water Distribution Networks. Journal of Hydraulic Engineering, 134(5), 626-635. doi:10.1061/(asce)0733-9429(2008)134:5(626)Islam, M. S., Sadiq, R., Rodriguez, M. J., Francisque, A., Najjaran, H., Naser, B., & Hoorfar, M. (2012). Evaluating leakage potential in water distribution systems: a fuzzy-based methodology. Journal of Water Supply: Research and Technology - Aqua, 61(4), 240-252. doi:10.2166/aqua.2012.151Kleiner, Y., & Rajani, B. (2002). Forecasting Variations and Trends in Water-Main Breaks. Journal of Infrastructure Systems, 8(4), 122-131. doi:10.1061/(asce)1076-0342(2002)8:4(122)Shamir, U., & Howard, C. D. D. (1979). An Analytic Approach to Scheduling Pipe Replacement. Journal - American Water Works Association, 71(5), 248-258. doi:10.1002/j.1551-8833.1979.tb04345.xWalski, T. M., & Pelliccia, A. (1982). Economic analysis of water main breaks. Journal - American Water Works Association, 74(3), 140-147. doi:10.1002/j.1551-8833.1982.tb04874.

Low-carbon scenarios for the Brazilian power system

The Brazilian power generation sector faces a paradigm change driven, on one hand, by a shift from a hydropower dominated mix and, on the other, by international goals for reducing greenhouse gases emissions. The objective of this work was to evaluate five scenarios for the Brazilian power system until 2050 using a multi-criteria decision analysis tool. These scenarios include a baseline trend and low carbon policy scenarios based on carbon taxes and carbon emission limits. To support the applied methodology, a questionnaire was elaborated to integrate the perceptions of experts on the scenario evaluation process. Taking into account the results from multi-criteria analysis, scenario preference followed the order of increasing share of renewables in the power system. The preferable option for the future Brazilian power system is a scenario where wind and biomass have a major contribution. The robustness of the multi-criteria tool applied in this study was tested by a sensitivity analysis. This analysis demonstrated that, regardless the respondents’ preferences and backgrounds, scenarios with higher shares of fossil fuel sources are the least preferable option, while scenarios with major contributions from wind and biomass are the preferable option to supply electricity in Brazil through 2050.This research was supported by a Marie Curie International Research Staff Exchange Scheme Fellowship within the 7th European Union Framework Programme, under project NETEP- European Brazilian Network on Energy Planning (PIRSES-GA-2013-612263)

Assessing supply chain risks in the automotive industry through a modified MCDM-based FMECA

Supply chains are complex networks that receive assiduous attention in the literature. Like any complex network, a supply chain is subject to a wide variety of risks that can result in significant economic losses and negative impacts in terms of image and prestige for companies. In circumstances of aggressive competition among companies, effective management of supply chain risks (SCR) is crucial, and is currently a very active field of research. Failure Mode Effects and Criticality Analysis (FMECA) has been recently extended to SCR identification and prioritization, aiming at reducing potential losses caused by lack of risk control. This article has a twofold objective. First, SCR assessment is investigated, and a comprehensive list of specific risks related to the automotive industry is compiled to extend the set of most commonly considered risks. Second, an alternative way of calculating the risk priority number (RPN) is proposed within the FMECA framework by means of an integrated multi-criteria decision-making (MCDM) approach. We give a new calculation procedure by making use of the Analytic Hierarchy Process (AHP) to derive factors weights, and then the fuzzy DEcision-MAking Trial and Evaluation Laboratory (DEMATEL) to evaluate the new factor of “dependence” among risks. The developed joint analysis constitutes a risk analysis support tool for criticality in systems engineering. The approach also deals with uncertainty and vagueness associated to input data through the use of fuzzy numbers. The results obtained from a relevant case study in the automotive industry showcase the effectiveness of this approach, which brings important value to those companies: when planning interventions of prevention/mitigation, primary importance should be given to 1) supply chain disruptions due to natural disasters, 2) manufacturing facilities, human resources, policies and breakdown processes, and 3) inefficient transport