Queuing network-based methodology for designing and assessing performance of centralized maintenance workshops

2014 ◽  
Vol 25 (4) ◽  
pp. 510-527 ◽  
Author(s):  
Zineb Simeu-Abazi ◽  
Maria Di Mascolo ◽  
Eric Gascard
Keyword(s):  
Sojourn Time ◽  
Decision Support Tool ◽  
Repair Process ◽  
Spare Parts ◽  
Modeling Framework ◽  
Corrective Maintenance ◽  
Content Type ◽  
Support Tool ◽  
Evaluation Of Performance ◽  
Replacement Technique

Purpose – In this paper, the authors are concerned with a maintenance workshop (MW) centralizing all corrective maintenance activities. The purpose of this paper is to propose a methodology for designing a central maintenance workshop, enabling the evaluation of performance in terms of cost and sojourn time, for a given budget. Design/methodology/approach – The authors propose a modeling framework based on queuing networks. The aim is to maximize operational availability of the production workshop, by reducing the sojourn time of failed equipment in the MW. Findings – The proposed methodology leads to a maintenance decision support tool enabling to give the structure of the MW, performing at a higher level, but at a reasonable configuration cost. Simulation results illustrate the influence of different parameters, such as the number of stations and the level of spare parts in the MW, on the sojourn time of the equipment. Research limitations/implications – Only corrective maintenance is taken into account and only equipment that can be taken out of the production workshop are considered. The preventive replacement of some equipment items can be taken into account by the repair process by considering them as failed. Originality/value – The work falls within a more general framework for optimizing maintenance costs, in the context of integration of multi-site services in a distributed context. The paper is concerned with centralized maintenance, and proposes to integrate the so-called repair by replacement technique in a MW, used for a multi-site production workshop.

Decision support for additive manufacturing deployment in remote or austere environments

2016 ◽  
Vol 27 (7) ◽  
pp. 898-914 ◽  
Author(s):  
Nicholas A. Meisel ◽  
Christopher B. Williams ◽  
Kimberly P. Ellis ◽  
Don Taylor
Keyword(s):  
Decision Support ◽  
Additive Manufacturing ◽  
Decision Support Tool ◽  
Spare Parts ◽  
Raw Material ◽  
Structured Interviews ◽  
Material Source ◽  
Content Type ◽  
Support Tool ◽  
Austere Environments

Purpose Additive manufacturing (AM) can reduce the process supply chain and encourage manufacturing innovation in remote or austere environments by producing an array of replacement/spare parts from a single raw material source. The wide variety of AM technologies, materials, and potential use cases necessitates decision support that addresses the diverse considerations of deployable manufacturing. The paper aims to discuss these issues. Design/methodology/approach Semi-structured interviews with potential users are conducted in order to establish a general deployable AM framework. This framework then forms the basis for a decision support tool to help users determine appropriate machines and materials for their desired deployable context. Findings User constraints are separated into process, machine, part, material, environmental, and logistical categories to form a deployable AM framework. These inform a “tiered funnel” selection tool, where each stage requires increased user knowledge of AM and the deployable context. The tool can help users narrow a database of candidate machines and materials to those appropriate for their deployable context. Research limitations/implications Future work will focus on expanding the environments covered by the decision support tool and expanding the user needs pool to incorporate private sector users and users less familiar with AM processes. Practical implications The framework in this paper can influence the growth of existing deployable manufacturing endeavors (e.g. Rapid Equipping Force Expeditionary Lab – Mobile, Army’s Mobile Parts Hospital, etc.) and considerations for future deployable AM systems. Originality/value This work represents novel research to develop both a framework for deployable AM and a user-driven decision support tool to select a process and material for the deployable context.

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

2017 ◽  
Vol 2650 (1) ◽  
pp. 74-83 ◽  
Author(s):  
Neda Masoud ◽  
Daisik Nam ◽  
Jiangbo Yu ◽  
R. Jayakrishnan
Keyword(s):  
Los Angeles ◽  
Travel Demand ◽  
Decision Support Tool ◽  
Peer To Peer ◽  
Successful Implementation ◽  
Modeling Framework ◽  
Transit System ◽  
Support Tool ◽  
Demand Shifts ◽  
Red Line

Peer-to-peer (P2P) ridesharing is a recently emerging travel alternative that can help accommodate the growth in urban travel demand and at the same time alleviate problems such as excessive vehicular emissions. Prior ridesharing projects suggest that the demand for ridesharing is usually shifted from transit, but its true benefits are realized when the demand shifts from single-occupancy vehicles. This study investigated the potential of shifting demand from private autos to transit by providing a general modeling framework that found routes for private vehicle users that were a combination of P2P ridesharing and transit. The Los Angeles Metro Red Line in California was considered for a case study because it has recently shown declining ridership trends. For successful implementation of a ridesharing system, strategically selecting locations for individuals to get on and off the rideshare vehicles is crucial, along with an appropriate pricing structure for the rides. The study conducted a parametric analysis of the application of real-time P2P ridesharing to feed the Los Angeles Metro Red Line with simulated demand. A mobile application with an innovative ride-matching algorithm was developed as a decision support tool that suggested transit-rideshare and rideshare routes.

Sustainable recovery for digital entrepreneurs with shared resources: enablers, challenges and solutions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ajay Jha ◽  
Rohit Sindhwani ◽  
Ashish Dwivedi ◽  
Venkataramanaiah Saddikuti
Keyword(s):  
Decision Support Tool ◽  
Emerging Economy ◽  
Sharing Economy ◽  
Shared Resources ◽  
Content Type ◽  
Support Tool ◽  
Study Approach ◽  
Criteria Weights ◽  
Topsis Technique ◽  
Sustainable Recovery

Purpose The purpose of this study is to identify important criteria for sustainable recovery of digital entrepreneurship from distress situation using shared resources. During pandemic disruption, the importance of sharing economy in managing business efficiency is reflected through this research. Design/methodology/approach The present study advances the knowledge on shared resources in business by integrating case study approach with multi criteria decision-making (MCDM) model. A fuzzy analytic hierarchy process approach is adopted to compute criteria weights, and a fuzzy technique for order performance by similarity to ideal solution (TOPSIS) technique is used to rank the sharing economy entrepreneurial ventures during COVID-19 pandemic in the context of emerging economy. Findings The present study identified five most important enablers (technological innovation, technology expertise, convergence of virtual and physical spaces, collaboration rather than competition, and benefits to underserved groups through transparency) for sustainable recovery of sharing economy ventures in emerging economy. For example, the study highlights online tutoring through shared intellect as the most sought after sharing economy venture during pandemic disruption, which fulfills the identified enablers. Practical implications The proposed framework provides an accurate decision support tool to rank the various identified potential enablers of sharing economy during disruptions. Further, the approach is practically relevant to sharing economy entrepreneurs in selecting the best approach to recover sustainability during pandemic. Originality/value The study is unique in addressing the need of sustainability for digital ventures via sharing economy approach in emerging economy (India). To develop a conceptual framework, the present study incorporates a case based approach together with the hybrid MCDM model. Further, the extant literature on disruptions is enhanced by prioritizing the enablers for sharing economy during pandemic.

Predictive data analytics for contract renewals: a decision support tool for managerial decision-making

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Design Science ◽  
Decision Support Tool ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Support Tool

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.

Benchmarking contractors’ financial performance: case study of Singapore

2020 ◽  
Vol 25 (2) ◽  
pp. 183-199 ◽  
Author(s):  
Zhe Zhang ◽  
Zhi Ye Koh ◽  
Florence Ling
Keyword(s):  
Decision Support ◽  
Decision Tree ◽  
Financial Performance ◽  
Decision Support Tool ◽  
International Standards ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Content Type ◽  
Support Tool ◽  
Public Agency

Purpose This study aims to develop benchmarks of the financial performance of contractors and a decision support tool for evaluation, selection and appointment of contractors. The financial benchmarks allow contractors to know where they are relative to the best-performing contractors, and they can then take steps to improve their own performance. The decision support tool helps clients to decide which contractor should be awarded the project. Design/methodology/approach Financial data between 2013 and 2015 of 44 Singapore-based contractors were acquired from a Singaporean public agency. Benchmarks for Z-score and financial ratios were developed. A decision tree for evaluating contractors was constructed. Findings This study found that between 57% and 64% of contractors stayed in the financially healthy zone from 2013 to 2015. Ratios related to financial liabilities are relatively bad compared with international standards. Research limitations/implications The limitation is that the data is obtained from a cross-sectional survey of contractors’ financial performance in Singapore over a three-year period. Regarding the finding that ratios relating to financial liabilities are weak, the implication is that contractors need to reduce their financial liabilities to achieve a good solvency profile. Contractors may use the benchmarks to check their financial performances relative to that of their competitors. To reduce financial risks, project clients may use these benchmarks to examine contractors’ financial performance. Originality/value This study provides benchmarks for contractors and clients to examine the financial performance of contractors in Singapore. A decision tree is provided to aid clients in making decisions on which contractors to appoint.

scholarly journals An innovative decision support tool for liquefied natural gas supply chain planning

2020 ◽  
Vol 5 (1) ◽  
pp. 121-136
Author(s):  
Christos Papaleonidas ◽  
Dimitrios V. Lyridis ◽  
Alexios Papakostas ◽  
Dimitris Antonis Konstantinidis
Keyword(s):  
Supply Chain ◽  
Decision Support ◽  
Natural Gas ◽  
Decision Support Tool ◽  
Liquefied Natural Gas ◽  
Maritime Transportation ◽  
Management Tool ◽  
Content Type ◽  
Support Tool ◽  
Tramp Shipping

Purpose The purpose of this paper is to improve the tactical planning of the stakeholders of the midstream liquefied natural gas (LNG) supply chain, using an optimisation approach. The results can contribute to enhance the proactivity on significant investment decisions. Design/methodology/approach A decision support tool (DST) is proposed to minimise the operational cost of a fleet of vessels. Mixed integer linear programming (MILP) used to perform contract assignment combined with a genetic algorithm solution are the foundations of the DST. The aforementioned methods present a formulation of the maritime transportation problem from the scope of tramp shipping companies. Findings The validation of the DST through a realistic case study illustrates its potential in generating quantitative data about the cost of the midstream LNG supply chain and the annual operations schedule for a fleet of LNG vessels. Research limitations/implications The LNG transportation scenarios included assumptions, which were required for resource reasons, such as omission of stochasticity. Notwithstanding the assumptions made, it is to the authors’ belief that the paper meets its objectives as described above. Practical implications Potential practitioners may exploit the results to make informed decisions on the operation of LNG vessels, charter rate quotes and/or redeployment of existing fleet. Originality/value The research has a novel approach as it combines the creation of practical management tool, with a comprehensive mathematical modelling, for the midstream LNG supply chain. Quantifying future fleet costs is an alternative approach, which may improve the planning procedure of a tramp shipping company.

The AEO status as a source of competitive advantage

2018 ◽  
Vol 30 (5) ◽  
pp. 591-606 ◽  
Author(s):  
Thierry Houé ◽  
Eileen Murphy
Keyword(s):  
Competitive Advantage ◽  
Balanced Scorecard ◽  
Decision Support Tool ◽  
Theoretical Background ◽  
Content Type ◽  
Support Tool ◽  
The Balanced Scorecard ◽  
Global Logistics ◽  
The Creation ◽  
Freight Forwarder

Purpose Faced with increasing competition, the ability to secure and optimise global logistics operations should be regarded as a competitive advantage. In the context of the hitherto little explored field of security and safety programmes, the purpose of this paper is to examine how an Authorised Economic Operator (AEO) certificate may affect the creation of a competitive edge for a freight forwarder. Design/methodology/approach By using the resource-based view as a theoretical background and a qualitative analysis using an interview grid inspired by the balanced scorecard, this research identifies resources and capabilities linked to the AEO certification. Findings The findings show two specific groups of resources that contribute to the creation of a competitive advantage. The first category is a process-type resource obtained through the AEO certification, which leads to more formalised and better-executed processes. The second relates to the freight forwarder’s knowledge, know-how and relational skills. Research limitations/implications This research is developed in a logistics service provider context. It should be equally applied in other contexts and with other methods to provide generalisability. Practical implications Considering its contribution to an area of study currently under research, the findings may be useful to practitioners as a decision support tool to assess the value of the AEO certification. Originality/value This paper comes in the context of a yet little explored field, despite practitioners’ questions about custom certifications.

Using a transport portfolio framework to reduce carbon footprint

2015 ◽  
Vol 26 (2) ◽  
pp. 296-312 ◽  
Author(s):  
Kristina Liljestrand ◽  
Martin Christopher ◽  
Dan Andersson
Keyword(s):  
Decision Support ◽  
Carbon Footprint ◽  
Quantitative Methods ◽  
Decision Support Tool ◽  
Load Factor ◽  
Theoretical Frameworks ◽  
Substantial Impact ◽  
Content Type ◽  
Support Tool ◽  
Modal Split

Purpose – The purpose of this paper is to develop a transport portfolio framework (TPF) and explore its use as a decision support tool for shippers wanting to improve their transport system in terms of reducing their carbon footprint. Design/methodology/approach – The TPF has been designed on the basis relevant theoretical frameworks in logistics and thereafter tested and further developed by the use of empirical data from a case study. Quantitative methods are used to find patterns in the shipment statistics for import flows obtained from a food retailer and carriers. Findings – The TPF highlights different avenues for decreasing the carbon footprint, by identifying the product flow characteristics that might affect modal split and load factor, and it is believed that these can help shippers’ intent on analysing the largest potential for improvement. This potential is estimated based on how the key variables, modal split and load factor, can be improved. Practical implications – Shippers can use the TPF as a decision support tool in their efforts to reduce their carbon footprint by: structuring complexity, managing data and finding effective solutions. Social implications – Reducing emissions is an increasingly important priority for shippers and the TPF helps them to direct their efforts towards approaches that have a substantial impact. Originality/value – The TPF provides an opportunity to match different approaches for improving the environmental performance with the potential for reducing carbon footprint in shippers’ transportation networks, by taking into account the complexity of logistics network.

Resiliency cube

2018 ◽  
Vol 9 (4/5) ◽  
pp. 317-332 ◽  
Author(s):  
Amirpurya Chavoshy ◽  
Kambod Amini Hosseini ◽  
Mahmood Hosseini
Keyword(s):  
Three Dimensional ◽  
Road Networks ◽  
Decision Support Tool ◽  
Analysis Model ◽  
Content Type ◽  
Support Tool ◽  
Earthquake Scenarios ◽  
Urban Road ◽  
Emergency Situations ◽  
Graphical Modelling

Purpose This study aims to provide resiliency against earthquakes to the framework of an urban road network and to construct a comprehensive model with sufficient computational detail to assist metropolitan managers as a decision support tool in emergency situations via parametric analysis (model behaviour analysis with parameter changes) to quantify the consequences of decisions. Design/methodology/approach Performed stages are: developing existing resilience assessment frameworks for use against earthquakes in urban road networks, identifying earthquake scenarios and estimating the weight of components using AHP, including an example modelling of Tehran; and developing modelling software (using Matlab®). Findings This study produced a software that performs three-dimensional (3D) graphical modelling, resiliency index measurements and its parametric analyses for the road networks against earthquakes. Based on this model, a prioritized list of upgrades is also introduced. The developed tool also addresses issues regarding the allocation of limited resources between the network components. Research limitations/implications Because of the novelty of the study, there is limited literature on this topic. Practical implications The developed model provides urban managers with a comprehensive list of upgrades and empowering them to graphically and numerically evaluate the resiliency changes as they alter the parameters of these measures and balance their decisions based on available funding. Originality/value In contrast to previous studies, this study has focused on all of these three keywords: resiliency, earthquake and road networks, and not only two of them.

A decision support tool to mitigate decision-making problems faced by a building design team

2017 ◽  
Vol 6 (1) ◽  
pp. 2-18 ◽  
Author(s):  
Natee Singhaputtangkul
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Tool ◽  
Building Design ◽  
Building Envelope ◽  
Design Team ◽  
Framework Analysis ◽  
Content Type ◽  
Support Tool

Purpose There are a number of decision-making problems encountered by a building design team. This issue is apparent in assessment of building envelope materials and designs in the early design stage. The purpose of this paper is to develope a decision support tool based on a quality function deployment (QFD) approach integrated with a knowledge management system (KMS) and fuzzy theory to facilitate a building design team to simultaneously mitigate the decision-making problems when assessing the building envelope materials and designs for the first instance. Design/methodology/approach This study engaged a design team comprising three decision makers (DMs) to test the developed decision support tool through a case study of a representative building project. The study employed deductive qualitative data analysis with use of a framework analysis approach to analyze perspectives of the DMs after completing the case study through a semi-structured interview. Findings A mapping diagram derived qualitatively from the framework analysis suggested that the tool can help mitigate the identified decision-making problems as a whole. Originality/value Practical contributions of using the decision support tool include achievement of a more efficient design and construction management, and higher productivity of a project. In terms of academic contributions, this study expands capabilities of a conventional decision support system, KMS, and QFD tool to handle decision-making problems.

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