Interval probability process mapping as a tool for drilling decisions analysis—the R&D perspective

Kevin Dodds; Alistair Fletcher

doi:10.1190/1.1766239

Appraisal of Apartments to be Rebuilt Using Real Options: Focused on the Model Considering the Probability Process of Price and Cost

Appraisal Studies ◽

10.23843/as.18.3.2 ◽

2019 ◽

Vol 18 (3) ◽

pp. 23-47

Author(s):

KwangChae Seo

Keyword(s):

Real Options ◽

Probability Process

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Understanding the importance of purchasing operations and identification of opportunities to increase their sustainability through process mapping

Prosperitas ◽

10.31570/prosp_2020_01_4 ◽

2020 ◽

Vol 7 (1) ◽

pp. 43-52

Author(s):

Marinko Maslaric ◽

Vojin Petrovic ◽

Gabriel Fedorko ◽

Svetlana Nikolicic ◽

Dejan Mircetic

Keyword(s):

Process Mapping

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Risk Assessment of Circuit Breakers Using Influence Diagrams with Interval Probabilities

Symmetry ◽

10.3390/sym13050737 ◽

2021 ◽

Vol 13 (5) ◽

pp. 737

Author(s):

Jelena D. Velimirovic ◽

Aleksandar Janjic

Keyword(s):

Power System ◽

Predictive Modelling ◽

Optimal Time ◽

Influence Diagrams ◽

Circuit Breakers ◽

Interval Probability ◽

Complex Power ◽

Interval Width ◽

Credal Sets ◽

The One

This paper deals with uncertainty, asymmetric information, and risk modelling in a complex power system. The uncertainty is managed by using probability and decision theory methods. More specifically, influence diagrams—as extended Bayesian network functions with interval probabilities represented through credal sets—were chosen for the predictive modelling scenario of replacing the most critical circuit breakers in optimal time. Namely, based on the available data on circuit breakers and other variables that affect the considered model of a complex power system, a group of experts was able to assess the situation using interval probabilities instead of crisp probabilities. Furthermore, the paper examines how the confidence interval width affects decision-making in this context and eliminates the information asymmetry of different experts. Based on the obtained results for each considered interval width separately on the action to be taken over the considered model in order to minimize the risk of the power system failure, it can be concluded that the proposed approach clearly indicates the advantages of using interval probability when making decisions in systems such as the one considered in this paper.

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A Novel Blind Signal Detector Based on the Entropy of the Power Spectrum Subband Energy Ratio

Entropy ◽

10.3390/e23040448 ◽

2021 ◽

Vol 23 (4) ◽

pp. 448

Author(s):

Han Li ◽

Yanzhu Hu ◽

Song Wang

Keyword(s):

Power Spectrum ◽

Detection Method ◽

Multinomial Distribution ◽

Sample Entropy ◽

Energy Ratio ◽

Statistical Characteristics ◽

Interval Probability ◽

Blind Signal ◽

Signal Detector ◽

Subband Energy

In this paper, we present a novel blind signal detector based on the entropy of the power spectrum subband energy ratio (PSER), the detection performance of which is significantly better than that of the classical energy detector. This detector is a full power spectrum detection method, and does not require the noise variance or prior information about the signal to be detected. According to the analysis of the statistical characteristics of the power spectrum subband energy ratio, this paper proposes concepts such as interval probability, interval entropy, sample entropy, joint interval entropy, PSER entropy, and sample entropy variance. Based on the multinomial distribution, in this paper the formulas for calculating the PSER entropy and the variance of sample entropy in the case of pure noise are derived. Based on the mixture multinomial distribution, the formulas for calculating the PSER entropy and the variance of sample entropy in the case of the signals mixed with noise are also derived. Under the constant false alarm strategy, the detector based on the entropy of the power spectrum subband energy ratio is derived. The experimental results for the primary signal detection are consistent with the theoretical calculation results, which proves that the detection method is correct.

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AB1131 STATISTICAL PROCESS CONTROL AND PROCESS MAPPING QUANTIFY THE EFFECTS OF HISTORICAL CHANGES TO THE CONNECTIVE TISSUE DISEASE TESTING ALGORITHM AND IDENTIFY AREAS FOR FUTURE IMPROVEMENT IN A LARGE DIAGNOSTIC IMMUNOLOGY SERVICE

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.438 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1855.2-1855

Author(s):

M. Stevens ◽

N. Proudlove ◽

J. Ball ◽

C. Scott

Keyword(s):

Process Control ◽

Statistical Process Control ◽

Control Charts ◽

Similar Proportion ◽

Limiting Factor ◽

List Type ◽

Process Mapping ◽

Statistical Process ◽

Current Testing ◽

Testing Algorithm

Background:Pathology test turnaround times (TATs) are a limiting factor in patient flow through rheumatology services. Quality improvement (QI) methodologies such as Lean use tools including statistical process control (SPC) and process mapping to study the performance of the whole of a clinical pipeline, expose unnecessary complexity (non-value-adding activity), and streamline processes and staff roles.Objectives:Understand effects of changes made to CTD testing algorithm over last 12 years by measuring some of the effects on TATs. Model current processes and suggest changes to workflow to improve TAT.Methods:High-level flow diagrams of the current testing algorithm, and low-level process maps of analyser and staff processes were drawn.Activity and TATs (working days between report and booking date) for ANA, ENA, DNA and CCP tests were plotted as XmR control charts.Results:Finding 1: Largest referral laboratory does not currently operate a separate DNA monitoring workstream, resulting in unnecessary ANA and ENA testing (figure 1).Figure 1.Current testing strategy (left) and suggested improvement (right)Finding 2:Samples are handed off between 3 different lab benches, each of which may be staffed by a different staff member on a different day, and results processing involves handoff to a further 2 different staff members.Finding 3:ANA demand is close to capacity, ENA demand exceeds current capacity (table 1).Table 1.Demand for ANA, ENA and DNA tests, compared to capacityTestMedian Demand(tests/ day)Approx. Capacity(tests/ day)NotesANA74100Close to 80% recommended by the ILGsENA3836*Less capacity than demand!!DNA34100PlentyFinding 4:Stopping screening DNA requests on ANA result increased the number of DNA tests performed by about 10 samples per day (30%), but decreased turnaround time by a similar proportion (3.3 to 2.3 days, figure 2). It also reduced turnaround times of ANA and ENA tests.Figure 2.Control chart of average TAT of dsDNA antibodies by request dateConclusion:Typically for a QI project, the initially simple CTD testing pipeline has accumulated many changes made without consideration of whole system performance, and is now a struggle to run.Improvement ideas to be explored from this work include:Liaising with main referral lab to develop a DNA monitoring workstream to reduce unnecessary ANA and ENA testingReduce handoffs, sample journey around lab analysers, and staff hands-on time by:changing ANA test methodology to same as DNAcreating new staff roles (analyser operators to perform validation/ authorisation steps)Create more capacity for ENA testing by increasing the frequency of this test on the weekly rotaCreate more capacity for service expansion by running analysers at weekends (staff consultation required)Reduce demand on service by engaging and educating requestorsImprove TAT for DNA by:processing samples the day they are booked in, instead of 1 day laterauto-validating runs…using control charts to measure improvementDisclosure of Interests:None declared

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Generalized Fokker–Planck equation with generalized interval probability

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2012.02.013 ◽

2013 ◽

Vol 37 (1-2) ◽

pp. 92-104 ◽

Cited By ~ 5

Author(s):

Yan Wang

Keyword(s):

Planck Equation ◽

Interval Probability ◽

Fokker Planck Equation ◽

Fokker Planck

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Mapping public value processes

International Journal of Public Sector Management ◽

10.1108/ijpsm-04-2013-0054 ◽

2014 ◽

Vol 27 (4) ◽

pp. 334-352 ◽

Cited By ~ 20

Author(s):

John Alford ◽

Sophie Yates

Keyword(s):

Public Sector ◽

Child Nutrition ◽

Process Mapping ◽

Public Value ◽

Public And Private ◽

Content Type ◽

The Public ◽

Public Managers ◽

Big Picture ◽

Comprehensive Framework

Purpose – The purpose of this paper is to add to the analytic toolkit of public sector practitioners by outlining a framework called Public Value Process Mapping (PVPM). This approach is designed to be more comprehensive than extant frameworks in either the private or public sectors, encapsulating multiple dimensions of productive processes. Design/methodology/approach – This paper explores the public administration and management literature to identify the major frameworks for visualising complex systems or processes, and a series of dimensions against which they can be compared. It then puts forward a more comprehensive framework – PVPM – and demonstrates its possible use with the example of Indigenous child nutrition in remote Australia. The benefits and limitations of the technique are then considered. Findings – First, extant process mapping frameworks each have some but not all of the features necessary to encompass certain dimensions of generic or public sector processes, such as: service-dominant logic; external as well internal providers; public and private value; and state coercive power. Second, PVPM can encompass the various dimensions more comprehensively, enabling visualisation of both the big picture and the fine detail of public value-creating processes. Third, PVPM has benefits – such as helping unearth opportunities or culprits affecting processes – as well as limitations – such as demonstrating causation and delineating the boundaries of maps. Practical implications – PVPM has a number of uses for policy analysts and public managers: it keeps the focus on outcomes; it can unearth a variety of processes and actors, some of them not immediately obvious; it can help to identify key processes and actors; it can help to identify the “real” culprits behind negative outcomes; and it highlights situations where multiple causes are at work. Originality/value – This approach, which draws on a number of precursors but constitutes a novel technique in the public sector context, enables the identification and to some extent the comprehension of a broader range of causal factors and actors. This heightens the possibility of imagining innovative solutions to difficult public policy issues, and alternative ways of delivering public services.

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