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.

scholarly journals Simulation-Based Decision Support System to Improve Material Flow of a Textile Company

2021 ◽  
Vol 13 (5) ◽  
pp. 2947
Author(s):  
Vítor Silva ◽  
Luís Pinto Ferreira ◽  
Francisco J. G. Silva ◽  
Benny Tjahjono ◽  
Paulo Ávila
Keyword(s):  
Decision Support ◽  
Material Flow ◽  
Control Strategies ◽  
Decision Support Tool ◽  
Raw Material ◽  
Support Tool ◽  
Point Of Entry ◽  
Work Area ◽  
Simulation Based ◽  
Positive Results

To remain competitive, companies must continuously improve the processes at hand, be they administrative, production, or logistics. The objective of the study described in this paper was to develop a decision-making tool based on a simulation model to support the production of knits and damask fabrics. The tool was used to test different control strategies for material flow, from the raw material warehouse to the finished product warehouse, and thus can also be used to evaluate the impacts of these strategies on the productivity. The data upon which the decision support tool was built were collected from five sectors of the plant: the raw material warehouse, knit production, damask production, finishing work, and the finished product warehouse. The decision support tool met the objectives of the project, with all five strategies developed showing positive results. Knit and damask production rates increased by up to 8% and 44%, respectively, and a reduction of 75% was observed in the waiting time on the point of entry to the finishing work area, compared to the company’s existing system.

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.

scholarly journals Model-Based Decision Support Tools at Jugos S.A. Concentrated Fruit Juice Plant

2020 ◽  
Vol 50 (4) ◽  
pp. 255-268
Author(s):  
Aníbal M. Blanco ◽  
M. Susana Moreno ◽  
Carolina Taraborelli ◽  
Flavio D’Angelo ◽  
Facundo Iturmendi ◽  
...  
Keyword(s):  
Decision Support ◽  
User Interfaces ◽  
Decision Support Tool ◽  
Raw Material ◽  
Mixed Integer ◽  
Support Tool ◽  
Support Tools ◽  
Optimal Target ◽  
And Storage

We describe the development of a decision-support tool to assist in the operations of a large concentrated apple and pear juice plant. The tool’s objective is to generate detailed schedules of clarified juice batches to be produced in the following weeks considering incoming fruit forecasts, commercial commitments, and infrastructural constraints. The tool is based on two interactive modules, PLANNER and SIMOPT, with different and complementary purposes. Each module is based on mixed-integer models with specific inputs, outputs, and user interfaces. PLANNER consists of three submodules: (i) planning assigns a batch of concentrated juice to be produced on a specific day, taking into account cleaning activities, rest days, raw material availability, and production and storage constraints; (ii) preprocessing organizes juice orders in batches; and (iii) pooling provides a detailed monitoring of semielaborated juice in storage pools in terms of inventories and sugar and acid content. Finally, SIMOPT provides a detailed optimal operative condition of the plant together with a thorough calculation of specific costs. This information is used by PLANNER to evaluate the corresponding economic objective functions. Besides providing optimal target conditions to the plant and feasible production schedules, the developed tools generate production guidelines in the long term and allow performing scenario studies.

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.

scholarly journals Identifying and selecting implementation theories, models and frameworks: a qualitative study to inform the development of a decision support tool

2020 ◽  
Author(s):  
Lisa Strifler ◽  
Jan M. Barnsley ◽  
Michael Hillmer ◽  
Sharon E. Straus
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
The United States ◽  
Theory Model ◽  
User Preferences ◽  
Tool Development ◽  
End User ◽  
Structured Interviews ◽  
Implementation Theory ◽  
Support Tool

Abstract Background: Implementation theories, models and frameworks offer guidance when implementing and sustaining healthcare evidence-based interventions. However, selection can be challenging given the myriad of potential options. We propose to develop a decision support tool to facilitate the appropriate selection of an implementation theory, model or framework in practice. To inform tool development, this study aimed to explore barriers and facilitators to identifying and selecting implementation theories, models and frameworks in research and practice, as well as end-user preferences for features and functions of the proposed tool.Methods: We used an interpretive descriptive approach to conduct semi-structured interviews with implementation researchers and practitioners in Canada, the United States and Australia. Audio recordings were transcribed verbatim. Data were inductively coded by a single investigator with a subset of 20% coded independently by a second investigator and analyzed using thematic analysis.Results: Twenty-four individuals participated in the study. Categories of barriers/facilitators, to inform tool development, included characteristics of the individual or team conducting implementation and characteristics of the implementation theory, model or framework. Major barriers to selection included inconsistent terminology, poor fit with the implementation context and limited knowledge about and training in existing theories, models and frameworks. Major facilitators to selection included the importance of clear and concise language and evidence that the theory, model or framework was applied in a relevant health setting or context. Participants were enthusiastic about the development of a decision support tool that is user-friendly, accessible and practical. Preferences for tool features included key questions about the implementation intervention or project (e.g., purpose, stage of implementation, intended target for change) and a comprehensive list of relevant theories, models and frameworks to choose from along with a glossary of terms and the contexts in which they were applied.Conclusions: An easy to use decision support tool that addresses key barriers to selecting an implementation theory, model or framework in practice may be beneficial to individuals who facilitate implementation practice activities. Findings on end-user preferences for tool features and functions will inform tool development and design through a user-centered approach.

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.

scholarly journals Identifying and selecting implementation theories, models and frameworks: a qualitative study to inform the development of a decision support tool

2020 ◽  
Author(s):  
Lisa Strifler ◽  
Jan M. Barnsley ◽  
Michael Hillmer ◽  
Sharon E. Straus
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
The United States ◽  
Theory Model ◽  
User Preferences ◽  
Tool Development ◽  
End User ◽  
Structured Interviews ◽  
Implementation Theory ◽  
Support Tool

Abstract Background: Implementation theories, models and frameworks offer guidance when implementing and sustaining healthcare evidence-based interventions. However, selection can be challenging given the myriad of potential options. We propose to inform a decision support tool to facilitate the appropriate selection of an implementation theory, model or framework in practice. To inform tool development, this study aimed to explore barriers and facilitators to identifying and selecting implementation theories, models and frameworks in research and practice, as well as end-user preferences for features and functions of the proposed tool.Methods: We used an interpretive descriptive approach to conduct semi-structured interviews with implementation researchers and practitioners in Canada, the United States and Australia. Audio recordings were transcribed verbatim. Data were inductively coded by a single investigator with a subset of 20% coded independently by a second investigator and analyzed using thematic analysis.Results: Twenty-four individuals participated in the study. Categories of barriers/facilitators, to inform tool development, included characteristics of the individual or team conducting implementation and characteristics of the implementation theory, model or framework. Major barriers to selection included inconsistent terminology, poor fit with the implementation context and limited knowledge about and training in existing theories, models and frameworks. Major facilitators to selection included the importance of clear and concise language and evidence that the theory, model or framework was applied in a relevant health setting or context. Participants were enthusiastic about the development of a decision support tool that is user-friendly, accessible and practical. Preferences for tool features included key questions about the implementation intervention or project (e.g., purpose, stage of implementation, intended target for change) and a comprehensive list of relevant theories, models and frameworks to choose from along with a glossary of terms and the contexts in which they were applied.Conclusions: An easy to use decision support tool that addresses key barriers to selecting an implementation theory, model or framework in practice may be beneficial to individuals who facilitate implementation practice activities. Findings on end-user preferences for tool features and functions will inform tool development and design through a user-centered approach.

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.

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