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.

scholarly journals Quality tracing in meat supply chains

2014 ◽  
Vol 372 (2017) ◽  
pp. 20130308 ◽  
Author(s):  
Miriam Mack ◽  
Patrick Dittmer ◽  
Marius Veigt ◽  
Mehmet Kus ◽  
Ulfert Nehmiz ◽  
...  
Keyword(s):  
Supply Chains ◽  
Process Analysis ◽  
Decision Support Tool ◽  
Temperature Monitoring ◽  
Support Tool ◽  
Logistics Network ◽  
Primary Model ◽  
Sensory Parameters ◽  
And Storage

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

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.

Spreadsheets as Knowledge Documents

2011 ◽  
pp. 521-537 ◽  
Author(s):  
Stephen Burgess ◽  
Don Schauder
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Small Business ◽  
Information Management ◽  
Explicit Knowledge ◽  
Decision Support Tool ◽  
Decision Support Tools ◽  
Support Tool ◽  
Applied Model ◽  
Support Tools

How should a small business decide whether and in what ways to use Web technology for interactions with customers? This case describes the creation of a practical decision support tool (using a spreadsheet) for the initiation and development of small business Web sites. Decisions arise from both explicit and tacit knowledge. Using selected literature from a structuration theory, information management and knowledge management, decision support tools are characterized as knowledge documents (communication agents for explicit knowledge). Understanding decision support tools as knowledge documents sheds light on their potentialities and limitations for knowledge transfer, and assists in maximizing their potentialities. The case study deploys three levels of modeling: a high-level structuration model of the interplay between information management and knowledge management, a conceptual model of small-business decision-making, and an applied model the practical decision support tool, itself. An action-research methodology involving experts and stakeholders validated the development of conceptual categories and their instantiation in the practical tool.

An online decision support tool to evaluate ecological weed management strategies

Weed Science ◽  
2019 ◽  
Vol 67 (4) ◽  
pp. 463-473
Author(s):  
Douglas Bessette ◽  
Robyn Wilson ◽  
Christian Beaudrie ◽  
Clayton Schroeder
Keyword(s):  
Decision Support ◽  
Soil Quality ◽  
Weed Management ◽  
Decision Support Tool ◽  
The United States ◽  
Support Tool ◽  
Organic Farmers ◽  
Ecological Weed Management ◽  
On Farm

AbstractWeeds remain the most commonly cited concern of organic farmers. Without the benefit of synthetic herbicides, organic farmers must rely on a host of ecological weed management (EWM) practices to control weeds. Despite EWM’s ability to improve soil quality, the perceived rate of integrated EWM strategy adoption remains low. This low adoption is likely a result of the complexity in designing and evaluating EWM strategies, the tendency for outreach to focus on the risks of EWM strategies rather than their benefits, and a lack of quantitative measures linking the performance of EWM strategies to farmers’ on-farm objectives and practices. Here we report on the development and deployment of an easy-to-use online decision support tool (DST) that aids organic farmers in identifying their on-farm objectives, characterizing the performance of their practices, and evaluating EWM strategies recommended by an expert advisory panel. Informed by the principles of structured decision making, the DST uses multiple choice tasks to help farmers evaluate the short- and long-term trade-offs of EWM strategies, while also focusing their attention on their most important objectives. We then invited organic farmers across the United States, in particular those whose email addresses were registered on the USDA’s Organic Research Integrity Database, to engage the DST online. Results show considerable movement in participants’ (n = 45) preferences from practices focused on reducing weeding costs and labor in the short term to EWM strategies focused on improving soil quality in the long term. Indeed, nearly half of those farmers (48%) who initially ranked a strategy composed of their current practices highest ultimately preferred a better-performing EWM strategy focused on eliminating the weed seedbank over 5 yr.

scholarly journals Reduction of the long-term use of proton pump inhibitors by a patient-oriented electronic decision support tool (arriba-PPI): study protocol for a randomized controlled trial

Trials ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Anja Rieckert ◽  
Annette Becker ◽  
Norbert Donner-Banzhof ◽  
Annika Viniol ◽  
Bettina Bücker ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Decision Support ◽  
Controlled Trial ◽  
Decision Support Tool ◽  
Routine Care ◽  
Electronic Decision Support ◽  
Support Tool ◽  
Randomized Controlled ◽  
Cluster Randomized

Abstract Background Proton pump inhibitors (PPIs) are increasingly being prescribed, although long-term use is associated with multiple side effects. Therefore, an electronic decision support tool with the aim of reducing the long-term use of PPIs in a shared decision-making process between general practitioners (GPs) and their patients has been developed. The developed tool is a module that can be added to the so-called arriba decision support tool, which is already used by GPs in Germany in routine care. In this large-scale cluster-randomized controlled trial we evaluate the effectiveness of this arriba-PPI tool. Methods The arriba-PPI tool is an electronic decision support system that supports shared decision-making and evidence-based decisions around the long-term use of PPIs at the point of care. The tool will be evaluated in a cluster-randomized controlled trial involving 210 GP practices and 3150 patients in Germany. GP practices will be asked to recruit 20 patients aged ≥ 18 years regularly taking PPIs for ≥ 6 months. After completion of patient recruitment, each GP practice with enrolled patients will be cluster-randomized. Intervention GP practices will get access to the software arriba-PPI, whereas control GPs will treat their patients as usual. After an observation period of six months, GP practices will be compared regarding the reduction of cumulated defined daily doses of PPI prescriptions per patient. Discussion Our principal hypothesis is that the application of the arriba-PPI tool can reduce PPI prescribing in primary care by at least 15% compared to conventional strategies used by GPs. A positive result implies the implementation of the arriba-PPI tool in routine care. Trial registration German Clinical Trials Register, DRKS00016364. Registered on 31 January 2019.

A decision-support tool to assist muscle-invasive bladder cancer patients choosing between radical cystectomy and chemoradiotherapy.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 505-505
Author(s):  
Brian Christopher Baumann ◽  
Wei-Ting Hwang ◽  
Sharadha Srinivasan ◽  
Xingmei Wang ◽  
Ronac Mamtani ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Decision Support ◽  
Decision Support Tool ◽  
Short Term ◽  
Muscle Invasive Bladder Cancer ◽  
Support Tool ◽  
Trade Offs ◽  
Muscle Invasive ◽  
Break Even Point

505 Background: Patients with high-risk muscle-invasive bladder cancer (MIBC) who are borderline medically operable for radical cystectomy (RC) face a difficult decision between RC which has higher short-term treatment-related morbidity/mortality & chemoradiotherapy (CRT) which is better tolerated in the short-term but may have worse long-term cancer control outcomes. There are no existing decision support tools to assist patients & providers in understanding these trade-offs. Herein, we developed a visualization tool to inform patients & providers how the relative risks & benefits of RC & CRT vary over time with respect to overall survival (OS). Methods: We identified cT2-3 N0 M0 urothelial bladder cancer patients ≥65 y/o treated with RC +/- chemo (n = 5981) or definitive-dose CRT after TURBT (n = 793) in the National Cancer Database, 2003-2011. The database was split into a development & validation cohort. Multivariate Cox regression with time-varying hazard ratio was performed to assess pre-treatment factors associated with OS. The inverse probability of treatment weighting method using the propensity score was employed to reduce selection bias. External validation was performed. Visualization tool showing adjusted survival curves based on pre-op patient features was generated with input from patients & a multidisciplinary expert panel. Tool calculates median OS & the “break-even point,” where the short-term OS disadvantage of RC equals the long-term advantage of RC (i.e. the point where the restricted mean survival for RC & CRT are equal). Results: On MVA, significant predictors of OS were age, Charlson Deyo comorbidity index, & cT stage (p < 0.001 for all). Using these results, we iteratively developed a web application that utilizes clinical inputs to generate patient-specific survival curves that display estimated OS differences over time. Median OS, the break-even point, & percent alive at the break-even point are provided. Conclusions: This is the first decision-support tool developed to assist high-risk borderline operable MIBC patients & their providers in understanding the short-term & long-term trade-offs between RC & CRT. Additional testing is underway.

Decision Support Tools in the Evaluation of Risk for Violence

2015 ◽  
Author(s):  
Adam J. E. Blanchard ◽  
Catherine S. Shaffer ◽  
Kevin S. Douglas
Keyword(s):  
Risk Assessment ◽  
Decision Support ◽  
Empirical Evaluation ◽  
Decision Support Tool ◽  
Assessment Instrument ◽  
Professional Judgment ◽  
Decision Support Tools ◽  
Support Tool ◽  
Risk Assessment Instrument ◽  
Support Tools

Professionals often utilize some form of structured approach (i.e., decision support tool or risk assessment instrument) when evaluating the risk of future violence and associated management needs. This chapter presents an overview of decision support tools that are used to assist professionals when conducting a violence risk assessment and that have received considerable empirical evaluation and professional uptake. The relative strengths and weaknesses of the two main approaches to evaluations of risk (actuarial and structured professional judgment) are discussed, including a review of empirical findings regarding their predictive validity. Following a summary of commonalities among the tools, this chapter provides a brief description of 10 decision support tools focusing on their applicability and purpose, content and characteristics, and available empirical research. Finally, the chapter concludes with a discussion of several critical considerations regarding the appropriate use and selection of tools.

scholarly journals Toward a User-Centered Design of a Weather Forecasting Decision-Support Tool

2017 ◽  
Vol 98 (2) ◽  
pp. 373-382 ◽  
Author(s):  
Elizabeth M. Argyle ◽  
Jonathan J. Gourley ◽  
Zachary L. Flamig ◽  
Tracy Hansen ◽  
Kevin Manross
Keyword(s):  
Decision Support ◽  
Weather Forecasting ◽  
Decision Support Tool ◽  
The United States ◽  
Usability Evaluation ◽  
Error Rates ◽  
Decision Support Tools ◽  
User Centered Design ◽  
Support Tool ◽  
Support Tools

ABSTRACT Hazard Services is a software toolkit that integrates information management, hazard alerting, and communication functions into a single user interface. When complete, National Weather Service forecasters across the United States will use Hazard Services for operational issuance of weather and hydrologic alerts, making the system an instrumental part of the threat management process. As a new decision-support tool, incorporating an understanding of user requirements and behavior is an important part of building a system that is usable, allowing users to perform work-related tasks efficiently and effectively. This paper discusses the Hazard Services system and findings from a usability evaluation with a sample of end users. Usability evaluations are frequently used to support software and website development and can provide feedback on a system’s efficiency of use, effectiveness, and learnability. In the present study, a user-testing evaluation assessed task performance in terms of error rates, error types, response time, and subjective feedback from a questionnaire. A series of design recommendations was developed based on the evaluation’s findings. The recommendations not only further the design of Hazard Services, but they may also inform the designs of other decision-support tools used in weather and hydrologic forecasting. Incorporating usability evaluation into the iterative design of decision-support tools, such as Hazard Services, can improve system efficiency, effectiveness, and user experience.

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 Risk of Suicide and Self-harm in Kids: The Development of an Algorithm to Identify High-Risk Individuals Within the Children’s Mental Health System

2020 ◽  
Vol 51 (6) ◽  
pp. 913-924 ◽  
Author(s):  
Shannon L. Stewart ◽  
Angela Celebre ◽  
John P. Hirdes ◽  
Jeffrey W. Poss
Keyword(s):  
Mental Health ◽  
Decision Support ◽  
Additional Data ◽  
Strong Predictor ◽  
Signs And Symptoms ◽  
Decision Support Tool ◽  
Support Tool ◽  
Increased Risk ◽  
Support Tools ◽  
Self Harm

Abstract Suicide is the second leading cause of death in adolescents within Canada. While several risk factors have been found to be associated with increased risk, appropriate decision-support tools are needed to identify children who are at highest risk for suicide and self-harm. The aim of the present study was to develop and validate a methodology for identifying children at heightened risk for self-harm and suicide. Ontario data based on the interRAI Child and Youth Mental Health Screener (ChYMH-S) were analyzed to develop a decision-support algorithm to identify young persons at risk for suicide or self-harm. The algorithm was validated with additional data from 59 agencies and found to be a strong predictor of suicidal ideation and self-harm. The RiSsK algorithm provides a psychometrically sound decision-support tool that may be used to identify children and youth who exhibit signs and symptoms noted to increase the likelihood of suicide and self-harm.

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