scholarly journals Decision Tools Regarding Time Constraints Violation in Manufacturing Workshops

2021 ◽  
Vol 16 (3) ◽  
Author(s):  
Nabil Jerbi ◽  
Simon Collart-Dutilleul
Keyword(s):  
Theoretical Result ◽  
Manufacturing System ◽  
Time Constraints ◽  
Simultaneous Occurrence ◽  
Time Petri Nets ◽  
Decision Tool ◽  
Robustness Property ◽  
Decision Tools ◽  
Two Delays ◽  
Operation Duration

This paper is dedicated to the study of constraints violation in manufacturing workshops with time constraints. In such systems, every operation duration is included between minimal and maximal values. P-time Petri nets are used for modeling. A new theorem is introduced, constituting a decision tool about the occurrence of constraints violation at the level of a synchronization transition when various types of time disturbances occur. It shows the robustness properties of a manufacturing system on a range that may include delay and advance disturbances. The theoretical result is illustrated step by step on a given workshop. Two other lemmas are elaborated contributing to the study of the constraints violation problem. The final goal is to generalize the robustness property towards simultaneous occurrence of two delays at two points of the system, each having its own robustness range.

scholarly journals Time Disturbances and Filtering of Sensors Signals in Tolerant Multi-product Job-shops with Time Constraints

2006 ◽  
Vol 1 (4) ◽  
pp. 61 ◽  
Author(s):  
Nabil Jerbi ◽  
Simon Collart Dutilleul ◽  
Etienne Craye ◽  
Mohamed Benrejeb
Keyword(s):  
Petri Nets ◽  
Critical Time ◽  
Time Constraints ◽  
Time Petri Nets ◽  
Quality And Safety ◽  
Localization Problem ◽  
Job Shops ◽  
Modeling Tool ◽  
Robustness Property

This paper deals with supervision in critical time manufacturing jobshops without assembling tasks. Such systems have a robustness property to deal with time disturbances. A filtering mechanism of sensors signals integrating the robustness values is proposed. It provides the avoidance of control freezing if the time disturbance is in the robustness intervals. This constitutes an enhancement of the filtering mechanism since it makes it possible to continue the production in a degraded mode providing the guarantees of quality and safety. When a symptom of abnormal functioning is claimed by the filtering mechanism, it is imperative to localize the time disturbance occurrence. Based upon controlled P-time Petri nets as a modeling tool, a series of lemmas are quoted in order to build a theory dealing with the localization problem.

A simulation model-based clinical decision tool to guide personalized treatment based on individual characteristics: Does 21-gene recurrence score assay testing change decisions?

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12507-e12507
Author(s):  
Jinani Jayasekera ◽  
Joseph A. Sparano ◽  
Young Chandler ◽  
Claudine Isaacs ◽  
Allison W. Kurian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Simulation Model ◽  
Early Stage ◽  
Clinical Decision ◽  
Distant Recurrence ◽  
Decision Tool ◽  
Decision Tools ◽  
Model Based ◽  
Life Years ◽  
Size Grade

e12507 Background: There is a need for web-based decision tools that integrate clinicopathologic features and genomic information to guide breast cancer therapy for women with node-negative, hormone receptor positive, HER2 negative (“early-stage”) breast cancer. We developed a novel simulation model-based clinical decision tool that provides prognostic estimates of treatment outcomes based on age, tumor size, grade, and comorbidities with and without 21-gene recurrence scores (RS). Methods: We adapted an extant breast cancer simulation model developed within the NCI-funded Cancer Intervention and Surveillance Modeling Network (CISNET) to derive estimates for the 10-year risks of distant recurrence, breast cancer-specific mortality, other cause mortality and life-years gained with endocrine vs. chemo-endocrine therapy for individual women based on their age, tumor size, grade, and comorbidity-level with and without RS test results. The model used an empiric Bayesian analytical approach to combine information from clinical trials, registry and claims data to provide individual estimates. External validation of the model was performed by comparing model-based breast cancer mortality rates and observed rates in the Surveillance Epidemiology and End Results (SEER) registry. Results: Several exemplar profiles were selected to illustrate the clinical utility of the decision tool. For example, the absolute chemotherapy benefit for 10-year distant recurrence risk and life-years gained, without RS testing, and the outcomes if a woman got tested and had a RS 16-20 are provided below for a 40-44-year-old woman and a 65–69-year-old woman diagnosed with a small (≤2cm), intermediate grade tumor and mild comorbidities. Conclusions: Simulation modeling is useful for creating clinical decision tools to support shared decision making for early-stage breast cancer treatment.[Table: see text]

Emphasizing Decision Analysis Techniques in the Design Curriculum

2001 ◽  
Author(s):  
Reid Bailey ◽  
Phil Doepker
Keyword(s):  
Utility Theory ◽  
Engineering Students ◽  
Ad Hoc ◽  
Decision Tool ◽  
Analysis Techniques ◽  
Decision Tools ◽  
Undergraduate Engineering ◽  
Senior Design ◽  
Factors Influencing

Abstract Theoretically strong decision approaches such as utility theory are currently being researched for use in engineering design. Countless ad hoc decision tools have preceded this recent work, yet only a handful of these tools are used by industry or taught in universities. Reasons for the emergence of such a small number of acceptable decision tools are not known. In this paper, the opinions of undergraduate engineering students in an industry-sponsored senior design class and their sponsor mentors are studied to identify reasons why some decision tools are more popular than others. Two established decision tools were introduced to the class and used in the projects. A survey was used to gather student and sponsor opinions about the two tools and important aspects of decision tools. Results indicate a variety of factors influencing the students’ preference of one decision tool, including simplicity, clarity of results, the ability to give more emphasis to certain criteria, and ease of communication of results to their sponsors. Other results from the study include information about strategies for integrating decision tools into a design process and the role of projects in promoting reflection and learning by students.

P-Time Petri Nets for Manufacturing Systems with Staying Time Constraints

1997 ◽  
Vol 30 (6) ◽  
pp. 1487-1492 ◽  
Author(s):  
Soizick Calvez ◽  
Pascal Aygalinc ◽  
Wael Khansa
Keyword(s):  
Petri Nets ◽  
Manufacturing Systems ◽  
Time Constraints ◽  
Time Petri Nets ◽  
Staying Time

scholarly journals Fuzzy Filtering of Sensors Signals in Manufacturing Systems with Time Constraints

2010 ◽  
Vol 5 (3) ◽  
pp. 362 ◽  
Author(s):  
Anis M’halla ◽  
Nabil Jerbi ◽  
Simon Collart Dutilleul ◽  
Etienne Craye ◽  
Mohamed Benrejeb
Keyword(s):  
Fuzzy Systems ◽  
Manufacturing Systems ◽  
Knowledge Integration ◽  
Expert Knowledge ◽  
Time Constraints ◽  
Quality And Safety ◽  
Job Shops ◽  
New Approach ◽  
Robustness Property ◽  
Filtering Approach

The presented work is dedicated to the supervision of manufacturing job-shops with time constraints. Such systems have a robustness property towards time disturbances. The main contribution of this paper is a fuzzy filtering approach of sensors signals integrating the robustness values. This new approach integrates a classic filtering mechanism of sensors signals and fuzzy logic techniques. The strengths of these both techniques are taken advantage of the avoidance of control freezing and the capability of fuzzy systems to deal with imprecise information by using fuzzy rules. Finally, to demonstrate the effectiveness and accuracy of this new approach, an example is depicted. The results show that the fuzzy approach allows keeping on producing, but in a degraded mode, while providing the guarantees of quality and safety based on expert knowledge integration.

scholarly journals Adaptive policies for use of physical distancing interventions during the COVID-19 pandemic

2020 ◽  
Author(s):  
Reza Yaesoubi ◽  
Joshua Havumaki ◽  
Melanie Chitwood ◽  
Nicolas A Menzies ◽  
Gregg Gonsalves ◽  
...  
Keyword(s):  
Real Time ◽  
Decision Rules ◽  
Social Costs ◽  
Surveillance Data ◽  
Decision Tool ◽  
Decision Tools ◽  
Model Based ◽  
Complex Models ◽  
Adaptive Policies

Policymakers need decision tools to determine when to use physical distancing interventions to maximize the control of COVID-19 while minimizing the economic and social costs of these interventions. We develop a pragmatic decision tool to characterize adaptive policies that combine real-time surveillance data with clear decision rules to guide when to trigger, continue, or stop physical distancing interventions during the current pandemic. In model-based experiments, we find that adaptive policies characterized by our proposed approach prevent more deaths and require a shorter overall duration of physical distancing than alternative physical distancing policies. Our proposed approach can readily be extended to more complex models and interventions.

scholarly journals Development and psychometric evaluation of the Transdiagnostic Decision Tool: matched care for patients with a mental disorder in need of highly specialised care

BJPsych Open ◽  
2020 ◽  
Vol 6 (5) ◽  
Author(s):  
Frédérique C. W. van Krugten ◽  
Christina M. van der Feltz-Cornelis ◽  
Manon A. Boeschoten ◽  
Saskia A. M. van Broeckhuysen-Kloth ◽  
Jonna F. van Eck van der Sluijs ◽  
...  
Keyword(s):  
Convergent Validity ◽  
Interrater Reliability ◽  
Mental Health Problems ◽  
Treatment Strategies ◽  
Area Under The Curve ◽  
Mental Healthcare ◽  
Psychometric Evaluation ◽  
Post Traumatic Stress ◽  
Decision Tool ◽  
Decision Tools

Background Early identification of patients with mental health problems in need of highly specialised care could enhance the timely provision of appropriate care and improve the clinical and cost-effectiveness of treatment strategies. Recent research on the development and psychometric evaluation of diagnosis-specific decision-support algorithms suggested that the treatment allocation of patients to highly specialised mental healthcare settings may be guided by a core set of transdiagnostic patient factors. Aims To develop and psychometrically evaluate a transdiagnostic decision tool to facilitate the uniform assessment of highly specialised mental healthcare need in heterogeneous patient groups. Method The Transdiagnostic Decision Tool was developed based on an analysis of transdiagnostic items of earlier developed diagnosis-specific decision tools. The Transdiagnostic Decision Tool was psychometrically evaluated in 505 patients with a somatic symptom disorder or post-traumatic stress disorder. Feasibility, interrater reliability, convergent validity and criterion validity were assessed. In order to evaluate convergent validity, the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the ICEpop CAPability measure for Adults (ICECAP-A) were administered. Results The six-item clinician-administered Transdiagnostic Decision Tool demonstrated excellent feasibility and acceptable interrater reliability. Spearman's rank correlations between the Transdiagnostic Decision Tool and ICECAP-A (−0.335), EQ-5D-5L index (−0.386) and EQ-5D-visual analogue scale (−0.348) supported convergent validity. The area under the curve was 0.81 and a cut-off value of ≥3 was found to represent the optimal cut-off value. Conclusions The Transdiagnostic Decision Tool demonstrated solid psychometric properties and showed promise as a measure for the early detection of patients in need of highly specialised mental healthcare.

scholarly journals Development of a Model-Informed Dosing Tool to Optimise Initial Antibiotic Dosing—A Translational Example for Intensive Care Units

Pharmaceutics ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2128
Author(s):  
Ferdinand Anton Weinelt ◽  
Miriam Songa Stegemann ◽  
Anja Theloe ◽  
Frieder Pfäfflin ◽  
Stephan Achterberg ◽  
...  
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Drug Exposure ◽  
Patient Characteristics ◽  
Initial Therapy ◽  
Decision Tool ◽  
Specific Patient ◽  
Decision Tools ◽  
Antibiotic Drug ◽  
Dosing Regimens

The prevalence and mortality rates of severe infections are high in intensive care units (ICUs). At the same time, the high pharmacokinetic variability observed in ICU patients increases the risk of inadequate antibiotic drug exposure. Therefore, dosing tailored to specific patient characteristics has a high potential to improve outcomes in this vulnerable patient population. This study aimed to develop a tabular dosing decision tool for initial therapy of meropenem integrating hospital-specific, thus far unexploited pathogen susceptibility information. An appropriate meropenem pharmacokinetic model was selected from the literature and evaluated using clinical data. Probability of target attainment (PTA) analysis was conducted for clinically interesting dosing regimens. To inform dosing prior to pathogen identification, the local pathogen-independent mean fraction of response (LPIFR) was calculated based on the observed minimum inhibitory concentrations distribution in the hospital. A simple, tabular, model-informed dosing decision tool was developed for initial meropenem therapy. Dosing recommendations achieving PTA > 90% or LPIFR > 90% for patients with different creatinine clearances were integrated. Based on the experiences during the development process, a generalised workflow for the development of tabular dosing decision tools was derived. The proposed workflow can support the development of model-informed dosing tools for initial therapy of various drugs and hospital-specific conditions.

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