Network resilience modelling: a New Zealand forestry supply chain case

2020 ◽  
Vol 31 (2) ◽  
pp. 291-311
Author(s):  
Paul Childerhouse ◽  
Mohammed Al Aqqad ◽  
Quan Zhou ◽  
Carel Bezuidenhout
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Supply Chains ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Network Resilience ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Event Simulation ◽  
Export Supply

PurposeThe objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.Design/methodology/approachThe research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.FindingsThe synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.Research limitations/implicationsThe two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single regionPractical implicationsNew Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.Originality/valueThe use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

scholarly journals Measuring lean implementation for maintenance service companies

2016 ◽  
Vol 7 (1) ◽  
pp. 35-61 ◽  
Author(s):  
Stephan J. de Jong ◽  
Wouter W.A. Beelaerts van Blokland
Keyword(s):  
Transaction Cost ◽  
Discrete Event Simulation ◽  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Discrete Event ◽  
Asset Specificity ◽  
Lean Implementation ◽  
Content Type ◽  
Event Simulation ◽  
Maintenance Service

Purpose – Implementation of lean manufacturing is currently performed in the production industry; however, for the airline maintenance service industry, it is still in its infancy. Indicators such as work in process, cycle time, on-time performance and inventory are useful indicators to measure lean implementation; however, a financial economic perspective taking fixed assets into consideration is still missing. Hence, the purpose of this paper is to propose a method to measure lean implementation from a fixed asset perspective for this type of industry. With the indicators, continuous improvement scenarios can be explored by value stream discrete event simulation. Design/methodology/approach – From literature, indicators regarding asset specificity to measure lean implementation are found. These indicators are analysed by a linear least square method to know if variables are interrelated to form a preliminary model. The indicators are tested by value stream-based discrete event simulation regarding continuous improvement scenarios. Findings – With the new found lean transaction cost efficiency indicators, namely, turnover, gross margin and inventory pre-fixed asset (T/FA, GM/FA and I/FA, respectively), it is possible to measure operation performance from an asset specificity perspective under the influence of lean implementation. Secondly, the results of implementing continuous improvement scenarios are measured with the new indicators by a discrete event simulation. Research limitations/implications – This research is limited to the airline maintenance, repair and overhaul (MRO) service industry regarding component repair. Further research is necessary to test the indicators regarding other airline MRO service companies and other sectors of complex service industries like health care. Practical implications – The lean transaction cost efficiency model provides the capability for a maintenance service company to simulate the effects of process improvements on operation performance for service-based companies prior to implementation. Social/implications – Simulation of a Greenfield process can involve employees with possible changes in processes. This approach supports the adoption of anticipated changes. Originality/value – The found indicators form a preliminary model, which contributes to the usage and linkage of theories on lean manufacturing and transaction cost theory – asset specificity.

Improving outpatient phlebotomy service efficiency and patient experience using discrete-event simulation

2016 ◽  
Vol 29 (7) ◽  
pp. 733-743 ◽  
Author(s):  
Kenneth Yip ◽  
Suk-King Pang ◽  
Kui-Tim Chan ◽  
Chi-Kuen Chan ◽  
Tsz-Leung Lee
Keyword(s):  
Discrete Event Simulation ◽  
Scenario Analysis ◽  
Performance Metrics ◽  
Discrete Event ◽  
Evidence Based ◽  
Content Type ◽  
Event Simulation ◽  
Service Efficiency ◽  
Related Service ◽  
The Relationship

Purpose – The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach – The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service’s final configuration via an evidence-based and data-driven approach. Findings – This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications – This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value – The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.

Supply chain resilience

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
Cutting Edge ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings COVID-19 has had a dramatic and damaging effect on supply chains and distributors. This briefing considers why, and what strategies there may be to cope. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Evaluation of postponement strategy in the production of table wine in Brazil: a discrete event simulation approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carolina Reis Gualberto ◽  
Lásara Fabrícia Rodrigues ◽  
Karine Araújo Ferreira
Keyword(s):  
Discrete Event Simulation ◽  
Discrete Event ◽  
Real Life ◽  
Minas Gerais ◽  
Future Research ◽  
Lost Sales ◽  
Wine Production ◽  
Content Type ◽  
Event Simulation ◽  
Postponement Strategy

Purpose The purpose of this paper is to develop an approach to evaluate the partial postponement strategy and compare it with postponement and make-to-stock (MTS) strategies in the production of table wine in wineries in the state of Minas Gerais (south-eastern Brazil). Design/methodology/approach An approach based on discrete event simulation was developed to support decision-making in the wine sector. Simulation models were used to analyse partial postponement, postponement and MTS strategies in wine production. These models were inspired by a typical table wine producer selected from an exploratory study conducted in 12 wineries of Minas Gerais state in Brazil. Findings Hybrid strategies, such as partial postponement, favour the advantages of postponement and MTS depending on the portion of semi-finished and finished goods adopted. Wine production characteristics favour postponement and partial postponement with high semi-finished product levels (customer order-driven product) because this allows companies to reduce their inventory of bottles, despite possible increases in lost sales and costs. MTS and partial postponement with high finished product levels (forecast-driven product) present higher costs with bottled wine storage; however, these strategies reduce lost sales and improve agility and reliability in deliveries. Research limitations/implications Future research should analyse the production of table wines in other regions of the country and the production of fine wines. Practical implications The findings suggest promising perspectives for real-life applications in wineries in Brazil and other countries. Originality/value Simulation techniques allow the analysis of production strategies in little-known industries, such as table wine production in Brazil. The approach developed is flexible enough to support decisions and to be adapted to companies’ and markets’ characteristics and to test specific strategies.

The structure of knowledge management in inter-organisational exchanges for resilient supply chains

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Umar ◽  
Mark Wilson ◽  
Jeff Heyl
Keyword(s):  
Knowledge Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Knowledge Generation ◽  
Collaborative Culture ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Food Supply Chains ◽  
Study Approach ◽  
Structure Of Knowledge

Purpose This study aims to build on the extant literature of knowledge management (KM) capabilities, notably infrastructure and processes, and examine how these capabilities influence the resilience of supply chains that experience regular natural disasters. Design/methodology/approach A multiple case study approach has been adopted to investigate the role of KM within foods supply chains of two different South Asian regions. This context was selected as these regions are prone to regular natural disruptions and these food supply chains also play a crucial role in the relief process. Findings The data shows that supply chain resilience can be enhanced when supply chain members collaborate to generate, share and use knowledge. These KM processes are greatly facilitated by KM infrastructure capabilities. IT advancements, a cohesive collaborative culture and the presence of strong central hubs firms in the network facilitate knowledge generation, knowledge sharing and knowledge utilisation, thus building supply chain resilience. Given the abductive nature of this research, these findings form the most likely associations, but with a degree of uncertainty. Hence, the authors provide propositions for further detailed research in this important area. Originality/value This study is one of the few, as far as the authors can tell, that seeks to examine the influence of KM on the resilience of supply chains. Further, uncovering the sub-structure of KM in this context adds to this emerging body of literature.

Supply chain resilience for vaccines: review of modeling approaches in the context of the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maureen S. Golan ◽  
Benjamin D. Trump ◽  
Jeffrey C. Cegan ◽  
Igor Linkov
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Securities And Exchange Commission ◽  
Matrix Analysis ◽  
Stress Tests ◽  
Critical Function ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Production And Distribution ◽  
The Face

PurposeDespite rapid success in bringing SARS-CoV-2 vaccines to distribution by multiple pharmaceutical corporations, supply chain failures in production and distribution can plague pandemic recovery. This review analyzes and addresses gaps in modeling supply chain resilience in general and specifically for vaccines in order to guide researchers and practitioners alike to improve critical function of vaccine supply chains in the face of inevitable disruptions.Design/methodology/approachSystematic review of the literature on modeling supply chain resilience from 2007 to 2020 is analyzed in tandem with the vaccine supply chain manufacturing literature. These trends are then used to apply a novel matrix analysis to seven Securities and Exchange Commission (SEC) annual filings of pharmaceutical corporations involved in COVID-19 vaccine manufacture and distribution.FindingsPharmaceutical corporations favor efficiency as they navigate regulatory, economic and other threats to their vaccine supply chains, neglecting resilience – absorption, adaptation and recovery from inevitable and unexpected disruptions. However, explicitly applying resilience analytics to the vaccine supply chain and further leveraging emerging network science tools found in the academic literature, such as artificial intelligence (AI), stress tests and digital twins, will help supply chain managers to better quantify efficiency/resilience tradeoffs across all associated networks/domains and support optimal system performance post disruption.Originality/valueThis is the first review addressing resilience analytics in vaccine supply chains and subsequent extension to operational management through novel matrix analyses of SEC Filings. The authors provide analyses and recommendations that facilitate resilience quantification capabilities for vaccine supply chain managers, regulatory agencies and corporate stakeholders and are especially relevant for pandemic response, including application to the SARS-CoV-2 vaccines.

scholarly journals The application of a hybrid simulation modelling framework as a decision-making tool for TPM improvement

2019 ◽  
Vol 25 (3) ◽  
pp. 476-498 ◽  
Author(s):  
Omogbai Oleghe ◽  
Konstantinos Salonitis
Keyword(s):  
Discrete Event Simulation ◽  
Hybrid Model ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Hybrid Modelling ◽  
Content Type ◽  
Event Simulation ◽  
Modelling Framework ◽  
Field Notes

Purpose The purpose of this paper is to promote a system dynamics-discrete event simulation (SD-DES) hybrid modelling framework, one that is useful for investigating problems comprising multifaceted elements which interact and evolve over time, such as is found in TPM. Design/methodology/approach The hybrid modelling framework commences with system observation using field notes which culminate in model conceptualization to structure the problem. Thereafter, an SD-DEShybrid model is designed for the system, and simulated to proffer improvement programmes. The hybrid model emphasises the interactions between key constructs relating to the system, feedback structures and process flow concepts that are the hallmarks of many problems in production. The modelling framework is applied to the TPM operations of a bottling plant where sub-optimal TPM performance was affecting throughput performance. Findings Simulation results for the case study show that intangible human factors such as worker motivation do not significantly affect TPM performance. What is most critical is ensuring full compliance to routine and scheduled maintenance tasks and coordinating the latter to align with rate of machine defect creation. Research limitations/implications The framework was developed with completeness, generality and reuse in view. It remains to be applied to a wide variety of TPM and non-TPM-related problems. Practical implications The developed hybrid model is scalable and can fit into an existing discrete event simulation model of a production system. The case study findings indicate where TPM managers should focus their efforts. Originality/value The investigation of TPM using SD-DES hybrid modelling is a novelty.

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