Enhancing the supply chain collaboration model in the Nigerian oil and gas industry : a case study of performance improvement strategies

This research focuses on the issues of supply chain collaboration in the oil and gas industry, specifically in Nigeria. global inflation, geopolitical events, logistic complexity, worldwide pandemics, cultural reorientation, information system difficulties, process integration, and organisational restructuring are among the listed challenges. There is a paucity of frameworks or models in the existing literature to handle these supply chain collaboration difficulties unique to the oil and gas sector. Four supply management theories (Resource Dependency Theory, Transaction Cost Theory, System Theory, and Network Theory) were employed to support the thesis. The researcher was motivated by personal experiences and realising the importance of the oil and gas sector to Nigeria's existence, the researcher seeks to investigate how supply chain collaboration might lead to industry performance improvement. The researcher is particularly interested in comprehending supply chain dynamics in the Nigerian oil and gas industry, as well as how collaboration might reduce obstacles associated with obtaining inputs. The purpose is to provide a steady supply of oil and gas products on the market, enhance operations, and address challenges caused by poor infrastructure and unclear government policies. A qualitative research method was used to fulfil these study aims, with an emphasis on gaining insights from managers and employees at four selected companies: NNPC, A. A. Rano, Total Nigeria, and Rain Oil. The obtained data was thematically analysed to identify significant pattern about supply chain collaboration leading to performance improvement. The study contributes to existing knowledge by identifying sixteen key findings, which include goal alignment, teamwork, performance management, relationship management, timeliness and order management, quality management, infrastructure, decision making, finance, COVID-19 pandemics, infrastructure development, poor leadership, process monitoring and evaluation, business strategy management, training and development, and good planning. Moreover, this study fills a gap in the literature by integrating these sixteen findings to develop a supply chain collaboration model as an effective strategy for mitigating supply chain challenges in the Nigerian oil and gas industry. The model was validated by managers from the participating companies, affirming its potential for performance improvement. In conclusion, this study helps better understand the difficulties the Nigerian oil and gas supply chain faces. It also includes a verified model that can be used to improve performance and offers insights into the advantages of supply chain collaboration. To further knowledge in this field, recommendations are provided for future studies, such as use of quantitative research method, comparative or mixed-method research, to further examine supply chain problems in the Nigerian oil and gas sector and related themes using case studies.This research focuses on the issues of supply chain collaboration in the oil and gas industry, specifically in Nigeria. global inflation, geopolitical events, logistic complexity, worldwide pandemics, cultural reorientation, information system difficulties, process integration, and organisational restructuring are among the listed challenges. There is a paucity of frameworks or models in the existing literature to handle these supply chain collaboration difficulties unique to the oil and gas sector. Four supply management theories (Resource Dependency Theory, Transaction Cost Theory, System Theory, and Network Theory) were employed to support the thesis. The researcher was motivated by personal experiences and realising the importance of the oil and gas sector to Nigeria's existence, the researcher seeks to investigate how supply chain collaboration might lead to industry performance improvement. The researcher is particularly interested in comprehending supply chain dynamics in the Nigerian oil and gas industry, as well as how collaboration might reduce obstacles associated with obtaining inputs. The purpose is to provide a steady supply of oil and gas products on the market, enhance operations, and address challenges caused by poor infrastructure and unclear government policies. A qualitative research method was used to fulfil these study aims, with an emphasis on gaining insights from managers and employees at four selected companies: NNPC, A. A. Rano, Total Nigeria, and Rain Oil. The obtained data was thematically analysed to identify significant pattern about supply chain collaboration leading to performance improvement. The study contributes to existing knowledge by identifying sixteen key findings, which include goal alignment, teamwork, performance management, relationship management, timeliness and order management, quality management, infrastructure, decision making, finance, COVID-19 pandemics, infrastructure development, poor leadership, process monitoring and evaluation, business strategy management, training and development, and good planning. Moreover, this study fills a gap in the literature by integrating these sixteen findings to develop a supply chain collaboration model as an effective strategy for mitigating supply chain challenges in the Nigerian oil and gas industry. The model was validated by managers from the participating companies, affirming its potential for performance improvement. In conclusion, this study helps better understand the difficulties the Nigerian oil and gas supply chain faces. It also includes a verified model that can be used to improve performance and offers insights into the advantages of supply chain collaboration. To further knowledge in this field, recommendations are provided for future studies, such as use of quantitative research method, comparative or mixed-method research, to further examine supply chain problems in the Nigerian oil and gas sector and related themes using case studies

Integrating Enterprise Decision-Making Modules into Undergraduate Management and Industrial Engineering Curricula

This paper describes a framework we have developed for teaching enterprise decision-making using Enterprise Decision-Making Modules linked together through a common case scenario. Each module is situated in an organizational process, e.g., the supply chain and order fulfillment process, and involves students in hands-on decision-making using an Enterprise System (ES) to provide an integrated, process-oriented, data-rich environment typical of modern organizations. Our framework differs from other approaches to integrating ES into curricula because it is designed to teach students to work in an integrated process-oriented environment without changing to an integrated process-oriented curriculum and because it introduces decision-making modules across management and engineering curricula while minimizing the ES knowledge required of faculty and the classroom time devoted to ES skills. The paper also describes our Oracle-based technical infrastructure, the project plan and management, as well as our methods for assessing student learning. It reports results from our successful pilot study testing the feasibility of this approach with two decision-making modules in two classes, and also describes Phase 2 of the project, currently underway, which involves additional faculty and modules and tests student understanding of working in an integrated, data-rich environment

Assessing and Selecting Sustainable and Resilient Suppliers in Agri-Food Supply Chains Using Artificial Intelligence: A Short Review

[EN] The supplier evaluation and selection process is critical to increase the sustainability and resilience of the agri-food supply chain. Therefore, in this sector, it is necessary to consider sustainability and resilience criteria in the supplier evaluation and selection process. The use of arti¿cial intelligence techniques allows managing of a lot of information and the reduction of uncertainty for decision making. The objective of this article is to analyze articles that address the selection of suppliers in agrifood supply chains that pursue to increase their sustainability and resilience by using arti¿cial intelligence techniques to analyze the techniques and criteria used and draw conclusions.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015.Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). Assessing and Selecting Sustainable and Resilient Suppliers in Agri-Food Supply Chains Using Artificial Intelligence: A Short Review. IFIP Advances in Information and Communication Technology. 598:501-510. https://doi.org/10.1007/978-3-030-62412-5_41S501510598Brandenburg, M., Govindan, K., Sarkis, J., Seuring, S.: Quantitative models for sustainable supply chain management: developments and directions. Eur. J. Oper. Res. 233, 299–312 (2014)Ocampo, L.A., Abad, G.K.M., Cabusas, K.G.L., Padon, M.L.A., Sevilla, N.C.: Recent approaches to supplier selection: a review of literature within 2006–2016. Int. J. Integr. Supply Manage. 12, 22–68 (2018)Valipour, S., Safaei, A.: A resilience approach for supplier selection: using Fuzzy analytic network process and grey VIKOR techniques. J. Clean. Prod. 161, 431–451 (2017)Amindoust, A.: A resilient-sustainable based supplier selection model using a hybrid intelligent method. Comput. Ind. Eng. 126, 122–135 (2018)Zavala-Alcívar, A., Verdecho, M.-J., Alfaro-Saiz, J.-J.: A conceptual framework to manage resilience and increase sustainability in the supply chain. Sustainability 12(16), 6300 (2020)Villalobos, J.R., Soto-Silva, W.E., González-Araya, M.C., González-Ramirez, R.G.: Research directions in technology development to support real-time decisions of fresh produce logistics: A review and research agenda. Comput. Electron. Agric. 167, 105092 (2019)Ristono, A., Santoso, P.B., Tama, I.P.: A literature review of design of criteria for supplier selection. J. Ind. Eng. Manage. 11, 680–696 (2018)Torres-Ruiz, A., Ravindran, A.R.: Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. J. Clean. Prod. 172, 4478–4493 (2018)Setak, M., Sharifi, S., Alimohammadian, A.: Supplier selection and order allocation models in supply chain management: a review. World Appl. Sci. J. 18, 55–72 (2012)Ravindran, A.R., Warsing, D.P.: Supplier selection models and methods. In: Supply Chain Engineering: Models and Applications. Taylor and Francis Group, Boca Raton, Florida (2013)De Boer, L., Labro, E., Morlacchi, P.: A review of methods supporting supplier selection. Eur. J. Purch. Supply Manage. 7, 75–89 (2011)De Felice, F., Deldoost, M.H., Faizollahi, M., Petrillo, A.: Performance measurement model for the supplier selection based on AHP. Int. J. Eng. Bus. Manag. 7, 1–13 (2015)Zimmer, K., Fröhling, M., Schultmann, F.: Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. Int. J. Prod. Res. 54, 1412–1442 (2016)Christopher, M., Peck, H.: Building the resilient supply chain. Int. J. Logist. Manag. 15, 1–14 (2014)Ali, A., Mahfouz, A., Arisha, A.: Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Manage. 22, 16–39 (2017)Verdecho, M., Alarcón-Valero, F., Pérez-Perales, D., et al.: A methodology to select suppliers to increase sustainability within supply chains. Cent. Eur. J. Oper. Res. (2020). https://doi.org/10.1007/s10100-019-00668-3Rabelo, L., Bhide, S., Gutierrez, E.: Artificial Intelligence: Advances in Research and Applications. Nova Science Publishers, Inc., Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, United States (2017)Denyer, D., Tranfield, D.: Producing a systematic review. In: The Sage Handbook of Organizational Research Methods. SAGE Publications Ltd., pp. 671–689 (2019)Chen, Y.-J.: Structured methodology for supplier selection and evaluation in a supply chain. Inf. Sci. (Ny) 181, 1651–1670 (2011)Hamdi, F., Ghorbel, A., Masmoudi, F., Dupont, L.: Optimization of a supply portfolio in the context of supply chain risk management: literature review. J. Intell. Manuf. 29(4), 763–788 (2015). https://doi.org/10.1007/s10845-015-1128-3Kumar, V., Srinivasan, S., Das, S.: Optimal solution for supplier selection based on SMART fuzzy case base approach. In: 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems. SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems. ISIS 2014, Institute of Electrical and Electronics Engineers Inc., Department of Computer Science, IISJ Yokohama, Tokai Chiba, Japan, pp. 386–391 (2014)Jahani, A., Murad, M.A.A., bin Sulaiman, M.N., Selamat, M.H.: An agent-based supplier selection framework: Fuzzy case-based reasoning perspective. Strateg. Outsourcing 8, 180–205 (2015)Wang, Q.: Hybrid knowledge-based flexible supplier selection. In: 8th International Conference on Management of e-Commerce and e-Government. ICMeCG 2014. Institute of Electrical and Electronics Engineers Inc., Department of Information Management, Shanghai Finance University, Shanghai, China, pp. 235–239 (2014)Bai, C., Sarkis, J.: Green supplier development: analytical evaluation using rough set theory. J. Clean. Prod. 18, 1200–1210 (2010)Bai, C., Sarkis, J.: Integrating sustainability into supplier selection with grey system and rough set methodologies. Int. J. Prod. Econ. 124, 252–264 (2010)Guo, F., Lu, Q.: Partner selection optimization model of agricultural enterprises in supply chain. Adv. J. Food Sci. Technol. 5, 1285–1291 (2013)Azadnia, A.H., Saman, M.Z.M., Wong, K.Y.: Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process. Int. J. Prod. Res. 53, 383–408 (2015)Miranda-Ackerman, M.A., Azzaro-Pantel, C., Aguilar-Lasserre, A.A.: A green supply chain network design framework for the processed food industry: application to the orange juice agrofood cluster. Comput. Ind. Eng. 109, 369–389 (2017)Hajikhani, A., Khalilzadeh, M., Sadjadi, S.J.: A fuzzy multi-objective multi-product supplier selection and order-allocation problem in supply chain under coverage and price considerations: an urban agricultural case study. Sci. Iran. 25, 431–449 (2018)Zhang, H., Cui, Y.: A model combining a Bayesian network with a modified genetic algorithm for green supplier selection. Simulation 95, 1165–1183 (2019)Yadav, S., Garg, D., Luthra, S.: Selection of third-party logistics services for internet of things-based agriculture supply chain management. Int. J. Logist. Syst. Manage. 35, 204–230 (2020)Yazdani, M., Wang, Z.X., Chan, F.T.S.: A decision support model based on the combined structure of DEMATEL, QFD and fuzzy values. Soft. Comput. 24(16), 12449–12468 (2020). https://doi.org/10.1007/s00500-020-04685-2Zhang, H., Feng, H., Cui, Y., Wang, Y.: A fuzzy Bayesian network model for quality control in O2O e-commerce. Int. J. Comput. Commun. Control 15(1), (2020). article number 1003. https://doi.org/10.15837/ijccc.2020.1.3783Amiri, S.A.H.S., Zahedi, A., Kazemi, M., Soroor, J., Hajiaghaei-Keshteli, M.: Determination of the optimal sales level of perishable goods in a two-echelon supply chain network. Comput. Ind. Eng. 139, 106156 (2020)Roy, S., et al.: A framework for sustainable supplier selection with transportation criteria. Int. J. Sustain. Eng. 13(2), 77–92 (2020)Parkouhi, S.V., Ghadikolaei, A.S., Lajimi, H.F.: Resilient supplier selection and segmentation in grey environment. J. Clean. Prod. 207, 1123–1137 (2019)Camarinha-Matos, L.M., Afsarmanesh, H., Galeano, N., Molina, A.: Collaborative networked organizations – concepts and practice in manufacturing enterprises. Comput. Ind. Eng. 57, 46–60 (2009)Lezoche, M., Panetto, H., Kacprzyk, J., Hernandez, J., Díaz, M.A.: Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture. Comput. Ind. 117, 103187 (2020)Alikhani, R., Torabi, S., Altay, N.: Strategic supplier selection under sustainability and risk criteria. Int. J. Prod. Econ. 208, 69–82 (2019

Customer Enquiry Management in a Global Competitive Context: A Comparative Multi-Case Study Analysis

Business-to-Business (B2B) relationships, such as between a manufacturer and a customer, are increasingly important during the Customer Enquiry Management (CEM) process, particularly so for non-Make-To-Stock (non-MTS) companies operating in industrial markets. Few empirical studies have explored the CEM practices adopted by firms in practice. A study of the Italian capital goods sector by Zorzini et al. (2007) is a recent exception. Moreover, most studies have approached CEM from a cross-department integrated perspective but in the digital economy, and with globalization, outsourcing and extended supply chains, CEM needs to be approached from a broader supply chain-oriented perspective, incorporating B2B exchanges. This paper builds on the study by Zorzini et al. (2007) by conducting multi-case study research with seven UK-based companies in the capital goods sector, including three sales and support companies with offshore manufacturing. By adopting a cross-national research perspective, it assesses whether the proposed theory applies to other capital goods firms outside Italy. By also adopting a supply chain perspective of CEM it investigates current industry practice in B2B markets and explores whether cross-functional coordination and formalization issues can be extended into a global context. Evidence from the UK generally supports prior theory, confirming links between high levels of coordination, formalization of the CEM process and improved performance. Some refinements are proposed, for example, in order to make the theory suitable for a global context. The characteristics of a supply chain are important factors that affect CEM. This research has managerial implications for improving the CEM process in non-Make-To-Stock (non-MTS) capital goods companies from both an intra and an inter-organisational (B2B) perspective. Coordination with partners along the supply chain is needed at the enquiry stage and constraints linked to global customers should be considered when structuring the

Lean and green – a systematic review of the state of the art literature

The move towards greener operations and products has forced companies to seek alternatives to balance efficiency gains and environmental friendliness in their operations and products. The exploration of the sequential or simultaneous deployment of lean and green initiatives is the results of this balancing action. However, the lean-green topic is relatively new, and it lacks of a clear and structured research definition. Thus, this paper’s main contribution is the offering of a systematic review of the existing literature on lean and green, aimed at providing guidance on the topic, uncovering gaps and inconsistencies in the literature, and finding new paths for research. The paper identifies and structures, through a concept map, six main research streams that comprise both conceptual and empirical research conducted within the context of various organisational functions and industrial sectors. Important issues for future research are then suggested in the form of research questions. The paper’s aim is to also contribute by stimulating scholars to further study this area in depth, which will lead to a better understanding of the compatibility and impact on organisational performance of lean and green initiatives. It also holds important implications for industrialists, who can develop a deeper and richer knowledge on lean and green to help them formulate more effective strategies for their deployment

Methodology for Designing Decision Support Systems for Visualising and Mitigating Supply Chain Cyber Risk from IoT Technologies

This paper proposes a methodology for designing decision support systems for visualising and mitigating the Internet of Things cyber risks. Digital technologies present new cyber risk in the supply chain which are often not visible to companies participating in the supply chains. This study investigates how the Internet of Things cyber risks can be visualised and mitigated in the process of designing business and supply chain strategies. The emerging DSS methodology present new findings on how digital technologies affect business and supply chain systems. Through epistemological analysis, the article derives with a decision support system for visualising supply chain cyber risk from Internet of Things digital technologies. Such methods do not exist at present and this represents the first attempt to devise a decision support system that would enable practitioners to develop a step by step process for visualising, assessing and mitigating the emerging cyber risk from IoT technologies on shared infrastructure in legacy supply chain systems

Selecting the right supply chain for a customer in project business : an action research study in the mobile communications infrastructure industry

This thesis is about integrating a supply chain to a customer's implementation project. The study is to identify and describe key factors that influence supply chain choices for project businesses. The aim is to explain the selection criteria for the right chain for an individual customer under different circumstances. The research problem, a highly relevant theme in the Internet age, is how to select the most appropriate supply chain for a customer in different business conditions. In addition to contributing to the scientific literature, this research also aims to support practical business situations in the industry by creating a normative decision-making model. The scope of this study is, thus, restricted to supply chains in project businesses where the success of logistics processes is largely dependent on how well physical deliveries are integrated into the implementation schedules of a project. The focused product type is typical of high-tech and innovative products with relatively short life cycles. Furthermore, the business environment of the scope is characterised by fast-growing turbulent markets. This study is an action research conducted in the GSM network business in Europe during 1999 and 2000. The research is an inductive, theory-building multiple-case study. The supplier case company is Nokia Networks, one of the leading suppliers of fixed and mobile telecommunication systems, and the customers consist of major European mobile phone operators, which however are anonymous in the thesis for the sake of business confidentiality. The research material was collected from customer-specific implementation projects that were individually carried out as part of an extensive supply chain re-engineering program inside the case company. The program, called BIRD (Breakthrough Inventory Rotation Days), aimed to streamline the process for high-volume base station deliveries and implement one of alternative supply solutions for a customer to best fit its individual needs. An individual process implementation for a customer (N=11) is considered to be the unit of analysis in this study. The basic axiom in the thesis is the Contingency Theory of Organisations that briefly says: "There is not one best way to organise something, but rather it depends on the environment". A customer's environmental requirements should determine the appropriate structure for the supply chain. The study maintains that there are two effective means to differentiate supply chain solutions for an individual customer. The first means is the well-known concept of Order Penetration Point (OPP). The second one is the value offering point (VOP), which is still a rather fresh and theoretical concept in the supply chain management literature. The study demonstrates how the positioning of these two points impact on the three dimensions of supply chains, i.e. on customer service, capital employment and total costs. The research results drawn from the in-depth case analysis are as follows: Three types of customer demand chains, distinguished by the position of the value offering point, can be identified among customers in project business. These are (1) call for project planning, (2) call for project execution and (3) call for project inventory management. Alternative supply chains are being used in different customer projects, quite intuitively, without a proper justification for the choices made. This is mainly due to contradictory target setting in project and supply chain systems (e.g., time buffers vs. material buffers) that makes it extremely complex to find the "right" supply chain solution for a customer. The accuracy of project planning and the implementation of a pre-defined execution trigger for ordering are actually sufficient selection factors to specify the right combination of value offering and order penetration points. However, as these selection factors are on a highly operational level, it is difficult to estimate their behaviour in a project beforehand. The technology life-cycle stage (which in this instance is represented by GSM penetration) and the level of the customer-supplier process collaboration are business conditions that can be used to estimate the behaviour of the selection factors in a project beforehand. Furthermore, these are considered to be necessary conditions in moving the value offering point further downstream in the chain. As a conclusion this study provides companies with a useful model to implement successful supply solutions for individual customers, especially applicable in the project business environment for innovative and high tech products. The study provides a set of normative rules to specify the right supply chain for a customer and defines the underlying pre-conditions to apply the rules. In addition to these normative results, the study provides new insight on the existing body of knowledge on integrating equipment deliveries into a customer's implementation project - which seems to be a fairly untouched area in the literature. According to the selected research approach, these conclusions are valid within the case study settings and their generalisation to a wider context should be further studied.reviewe

Clusters and supply chain management: challenges and obstacles

Purpose: This paper provides an insight into cluster supply chain (CSC) management by identifying challenges and obstacles in the design, implementation and improvement of CSC. This evaluation aims to propose future research directions for the management of CSC. Research Approach: A systematic review of published research on CSC management between 2006 and 2013 is conducted in order to round up previous research in this area and identify the gaps in the design, implementation and management of CSC; up on which the paper closes with a proposed agenda for future work. Findings and Originality: There is a limited understanding of the supply chain cluster concept and the implementation of its practices in addition to the lack of studies that focused on how to model, manage and improve the performance of CSC. Therefore, this paper would contribute to knowledge by providing an insight into CSC management and identifying future research directions for developing SC cluster theories in order to maximize the integration of supply chain and accordingly improving the performance of firms. Research Impact: A limited number of studies have been conducted to demonstrate the potential impact of CSC. The previous research did not provide a comprehensive review focusing on the evolution and the development of CSC idea. The review in this paper will summarise the research up to now in CSC area in order to identify challenges and obstacles in the design, implementation and improvement of CSC and propose future research directions. Practical Impact: This paper helps companies to understand benefits that can be raised from creating CSC and gives them directions for improving their capabilities to create CSC and select SC partners, which consequently help in increasing their competitiveness in terms of enhancing performance and increasing sustainability

Cost Risk Management for a Small to Medium-sized Enterprise in the Cladding Industry

To research the management of risk and cost in the cladding industry, this work has evaluated current practice and deficiencies, concentrating on the lack of integration or standardisation resulting in inaccurate cost estimates, unacceptable risks and loss of profit in cladding manufacture. The research presents an approach for integrating process- and technology-orientated improvements into a knowledge-based model to improve a cladding manufacturing SME’s performance. The research also presents a management method for the selection, integration, control and implementation of this approach. Controlling data transfer between systems produces a knowledge-based model, allowing cladding industry designers and estimators to take more accurate decisions, with the objective of reducing risk and improving company profitability. This model, with the addition of external supply chain elements, is a management framework, which can be termed an agile manufacturing system. The development of this framework has raised the following data certainty questions: • What is the measured uncertainty of that data? • How can the industry control and structure high data volumes transferred between systems to produce more accurate cost models? The answers to these questions were found by applying a structured methodology for the selection, integration and control of technology in the cladding industry, but involving the human factor. In this approach, the principle of entropy was adopted to measure data uncertainty. The structured methodology was made possible by a new categorisation into Innovative, Standard and Semi-Standard cladding projects. The research applied this structured methodology, combining qualitative and quantitative methods for validating assumptions, to a cladding industry SME case-study. The case-study investigated the validity of real cost and project data and calculated data uncertainty for specific projects, categorised as described, using a risk factor percentage predicted on entropy principles, based on historical data fed back from the SME’s ERP system. This risk factor approach was similar to that previously used in the insurance and banking industries. The risk percentage formulae used were based on assumptions extracted from qualitative and quantitative methods applied to the SME, its partner companies and industry specialists. Assumptions about the gross margins for UK metal cladding projects formed part of the risk percentage formulae. The results of this case-study found that gross margins varied from 5% in standard projects to 40% in the Innovative projects. An entropy scale was proposed as a basis for comparing risk calculation results, with the highest entropy equalling 100%, signifying the highest risk possible. It was found that risk rises in the case-study were from 23% for Standard to 93% for Innovative projects. This principle of a risk factor percentage was tested in the UK cladding manufacturer SME case-study and its value to the SME was demonstrated.

Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system