1) Condition monitoring of transmission and distribution networks is important to reduce outage costs and ensure reliable electricity delivery. It helps identify equipment failures early to plan maintenance and avoid unplanned outages.
2) When selecting a condition monitoring method, utilities must balance costs of the monitoring technique against costs of missed failures and false alarms. Continuous online monitoring detects more failures but yields more false alarms than periodic monitoring.
3) A full asset management process involves setting performance standards, assessing asset condition and risks, prioritizing maintenance based on condition and risk levels, and planning work accordingly. This helps utilities optimize maintenance planning and budgets.
This document provides guidance on planning and conducting a measurement system analysis (MSA). It discusses determining what to measure, selecting MSA tools, identifying participants, acquiring sample products, and developing a study plan. Key steps include identifying critical outputs and inputs from a cause-and-effect matrix, using 3 operators to test reproducibility, selecting 10-20 random samples as a "master" dataset, and distributing samples and collection instructions to operators without calibrating the measurement system during the MSA. The goal is to reflect the true "as-is" measurement process capabilities.
This document discusses challenges and best practices for CAPA (corrective and preventative action) programs. It outlines common pitfalls such as implementing actions that don't address the root cause, focusing on timelines over deliverables, and overusing "operator error" as a root cause. Best practices include using a multidisciplinary team approach, evaluating trends, and identifying all relevant inputs to the CAPA process. Effectiveness is best measured by metrics like recurrence rates and timeliness rather than just pass rates of proof of effectiveness. The document provides guidance on how to conduct a robust CAPA process.
1) The document discusses implementing a condition-based monitoring program for mechanical assets at power plants to improve reliability. It recommends transitioning from reactive maintenance to using continuous monitoring and automation.
2) It outlines a 3-step process: prioritizing critical assets, applying continuous condition monitoring technologies, and analyzing data to evaluate asset health and detect problems early.
3) The document provides examples of common asset failure modes and recommends monitoring pumps, fans, and other rotating equipment in addition to turbines to improve availability.
Using FMEA as a Risk Management Tool for Events SustainabilityPECB
When planning an event, we have to take into consideration issues such as environmental, social and economic. Actions need to be taken to address risks and opportunities. We need to establish the ways how to identify and evaluate them.
The webinar covers:
• Planning for Events Sustainability
• Risk Management Process for Sustainability
• Advantages of using the FMEA Risk Score
Presenter:
This webinar was hosted by PECB Certified Trainer and Founder/ CEO at Powerhouse Development and Coaching Academy, Ms. Mary Anne Concio.
Link of the recorded webinar published on YouTube: https://youtu.be/4IamxVdji9o
The document outlines three primary steps in maintenance reliability engineering:
1. Measure availability and identify failure-prone equipment by calculating metrics like MTBF, MTTR, and MLDT.
2. Perform root cause failure analysis to determine the underlying causes of failures and their costs.
3. Develop and implement corrective job plans using reliability centered maintenance principles to eliminate causes and manage failures, aimed at increasing availability and reducing costs over time.
CAPA, Root Cause Analysis and Risk ManagementJoseph Tarsio
This document discusses various quality management tools used for corrective and preventative action (CAPA), including root cause analysis. It describes CAPA and its regulatory requirements. Various tools for root cause analysis are explained, including the five whys technique, fishbone diagrams, Pareto charts, fault tree analysis, and failure mode and effects analysis. FMEA involves calculating a risk priority number to identify high-risk failures for corrective action. The document emphasizes the importance of identifying root causes of problems in order to implement effective preventative actions and reduce risks.
This document provides guidance on planning and conducting a measurement system analysis (MSA). It discusses determining what to measure, selecting MSA tools, identifying participants, acquiring sample products, and developing a study plan. Key steps include identifying critical outputs and inputs from a cause-and-effect matrix, using 3 operators to test reproducibility, selecting 10-20 random samples as a "master" dataset, and distributing samples and collection instructions to operators without calibrating the measurement system during the MSA. The goal is to reflect the true "as-is" measurement process capabilities.
This document discusses challenges and best practices for CAPA (corrective and preventative action) programs. It outlines common pitfalls such as implementing actions that don't address the root cause, focusing on timelines over deliverables, and overusing "operator error" as a root cause. Best practices include using a multidisciplinary team approach, evaluating trends, and identifying all relevant inputs to the CAPA process. Effectiveness is best measured by metrics like recurrence rates and timeliness rather than just pass rates of proof of effectiveness. The document provides guidance on how to conduct a robust CAPA process.
1) The document discusses implementing a condition-based monitoring program for mechanical assets at power plants to improve reliability. It recommends transitioning from reactive maintenance to using continuous monitoring and automation.
2) It outlines a 3-step process: prioritizing critical assets, applying continuous condition monitoring technologies, and analyzing data to evaluate asset health and detect problems early.
3) The document provides examples of common asset failure modes and recommends monitoring pumps, fans, and other rotating equipment in addition to turbines to improve availability.
Using FMEA as a Risk Management Tool for Events SustainabilityPECB
When planning an event, we have to take into consideration issues such as environmental, social and economic. Actions need to be taken to address risks and opportunities. We need to establish the ways how to identify and evaluate them.
The webinar covers:
• Planning for Events Sustainability
• Risk Management Process for Sustainability
• Advantages of using the FMEA Risk Score
Presenter:
This webinar was hosted by PECB Certified Trainer and Founder/ CEO at Powerhouse Development and Coaching Academy, Ms. Mary Anne Concio.
Link of the recorded webinar published on YouTube: https://youtu.be/4IamxVdji9o
The document outlines three primary steps in maintenance reliability engineering:
1. Measure availability and identify failure-prone equipment by calculating metrics like MTBF, MTTR, and MLDT.
2. Perform root cause failure analysis to determine the underlying causes of failures and their costs.
3. Develop and implement corrective job plans using reliability centered maintenance principles to eliminate causes and manage failures, aimed at increasing availability and reducing costs over time.
CAPA, Root Cause Analysis and Risk ManagementJoseph Tarsio
This document discusses various quality management tools used for corrective and preventative action (CAPA), including root cause analysis. It describes CAPA and its regulatory requirements. Various tools for root cause analysis are explained, including the five whys technique, fishbone diagrams, Pareto charts, fault tree analysis, and failure mode and effects analysis. FMEA involves calculating a risk priority number to identify high-risk failures for corrective action. The document emphasizes the importance of identifying root causes of problems in order to implement effective preventative actions and reduce risks.
This complete presentation has a set of thirty two slides to show your mastery of the subject. Use this ready-made PowerPoint presentation to present before your internal teams or the audience. All presentation designs in this Risk Analysis PowerPoint Presentation Slides have been crafted by our team of expert PowerPoint designers using the best of PPT templates, images, data-driven graphs and vector icons. The content has been well-researched by our team of business researchers. The biggest advantage of downloading this deck is that it is fully editable in PowerPoint. You can change the colors, font and text without any hassle to suit your business needs.
This document provides an overview of risk analysis. It defines key terms like risk, risk analysis, risk assessment, and risk management. It describes various qualitative and quantitative methods used for risk analysis, including hazard and operability studies, fault tree analysis, failure mode and effects analysis. The document discusses the importance of risk analysis for chemical processes and highlights some historical accidents to emphasize this. It also provides examples of applying different risk analysis methods.
The document discusses various quality management tools used for corrective and preventative action (CAPA), including root cause analysis. It defines CAPA and explains that it is required to eliminate existing nonconformities and prevent their recurrence. Various regulatory guidance on CAPA is referenced. Tools for root cause analysis discussed include the five whys technique, fishbone diagrams, Pareto charts, and fault tree analysis. Steps for conducting the five whys technique and creating fishbone diagrams are outlined. Advantages and limitations of fishbone diagrams and Pareto charts are also summarized.
This document provides an evaluation of preventative technologies for Kangaroo Inc., a dental software company. It identifies the top risks as patching, outdated firewalls, BYOD, backup failures, and lack of change control. A failure modes and effects analysis identifies patching as a major risk due to staff turnover and system diversity. The outdated firewall lacks vendor support and regional offices have expired intrusion detection. Recommendations are provided to reduce residual risks through improved patching, new firewalls, BYOD policies, backup solutions, and change control procedures.
A CAPA (Corrective and Preventive Action plan) is written to address problems identified in clinical research studies. It outlines the root cause of the problem, corrective actions taken to resolve the issue, and preventive measures to avoid future occurrences. The CAPA should be authored by the responsible party, focus on solutions rather than blame, and include a root cause analysis, corrective actions, and preventive actions. It follows a specific template that provides the issue, analyses, resolutions and plans for evaluation. The completed CAPA is submitted to the IRB and site monitors to document handling of issues.
The document discusses how to specify requirements for critical systems based on risk analysis. It explains how to identify risks, analyze and classify them, then derive safety, security, and reliability requirements to reduce risks. For reliability, it describes metrics like probability of failure on demand and mean time to failure that can be used to specify quantitative reliability levels. The goal is to develop requirements that eliminate intolerable risks and minimize other risks given cost and schedule constraints.
Corrective and Preventative Action (CAPA) is a system of quality procedures required to eliminate the causes of an existing nonconformity and to prevent recurrence of nonconforming product, processes, and other quality problems.
eCompliance, Cameron Freese_Measuring and Communicating Safety PerformanceeCompliance
Performance can be measured in many ways, but the
choice of which metrics and how to communicate these
effectively across the organization, play an important
role in establishing a strong safety culture and overall
management system. Explore how Aecon uses leading
and lagging indicators across their business to identify
themes or trends and take action.
The document discusses Failure Mode and Effects Analysis (FMEA), a systematic method for evaluating processes and identifying risks and failures. It describes the FMEA steps which include selecting a process, assembling a team, identifying potential failures and causes, analyzing severity, occurrence, detection and calculating a risk priority number. The document also notes some limitations and reasons FMEAs may fail, such as not involving all team members or getting bogged down in details.
Reducing Product Development Risk with Reliability Engineering MethodsWilde Analysis Ltd.
Overview of how reliability engineering methodology and software tools can help companies manage risk during product development and improve performance.
Presented at the Interplas'2011 exhibition and conference at the NEC on 27th October 2011 by Mike McCarthy.
This presentation looks at how ‘Reliability Engineering’ tools and methods are used to reduce risk in a typical product development lifecycle involving both plastic and metallic components. These tools range in complexity from simple approaches to managing product reliability data to the application of sophisticated simulation methods on large systems with complex duty cycles. Three examples are:
- Failure Mode Effects (and Criticality) Analysis (FMECA) to identify, manage and reuse information on what could go wrong with a design or manufacturing process and how to avoid it
- Design of Experiments for optimising performance through a structured and efficient study of parameters that affect the product or manufacturing process (e.g. injection moulding)
- Accelerated Life Testing to identify potential long term failure modes of products released to market within a shortened development time.
We will explore how gathering enough of the right kind of data and applying it in an intelligent way can reduce risk, not only in plastic product design and manufacture, but also in managing the associated supply chain and in the ‘Whole Life Management’ of products (including warranties). Furthermore, we will show how ‘sparse’ data gathered from previous or similar products, such as field/warranty reports, engineering testing data and supplier data sheets, as well as FEA, CFD and injection moulding/extrusion simulation, can inform and positively influence new product design processes from concept stage onwards.
This presentation explores the challenges, opportunities and available tools in developing a safety case regime for operators of major hazardous installations.
An analyst's perspective on measuring safety performance, discussing reactive and proactive indicators, ideas on developing proactive indicators, and a balanced scorecard approach to safety metrics
How to Measure the Relevance and Accuracy of OHS Informationdanieljohn810
This document discusses how to measure the accuracy and relevance of occupational health and safety (OHS) information. It explains that information must be reliable, valid, current and complete to be accurate. Several common OHS performance measures are examined, including safety meetings held, audits completed, and exposures exceeding standards. However, the document notes that the validity and reliability of these measures depends on clearly defining what is being measured, the data collection method, and the link to actual OHS performance. Factors like sample size, measurement protocols, and criteria for things like "close out" need consideration. The source and currency of information also impact accuracy and relevance.
This document discusses hazard analysis and risk assessment. It defines hazard and risk, and outlines the main steps in hazard analysis and risk assessment. These include identifying hazards, determining who may be harmed and how, assessing dose-response and exposure, risk management and control. Hazard analysis techniques include checklists, safety audits, preliminary hazard analysis, failure modes and effects analysis, what-if analysis, and hazard and operability studies. Risk assessment involves quantifying risk based on probability and severity. The document emphasizes that hazard analysis and risk assessment should be ongoing processes throughout the lifecycle of a system.
rrelic has developed a highly effective Total Reliability Framework for the implementation of reliability methods, tools and services in order to achieve your desired end results.
Total reliability Framework (TRF) Provides a management system for all reliability and Maintenance activities; focus on improving the performance of both the personnel and the plant equipment.
Reliability Centered Maintenance (RCM) is a process that determines the best policies for managing asset functions and failures. It considers all asset management options like condition monitoring, scheduled restoration, and scheduled discard. RCM provides the optimal mix of reactive, time-based, condition-based, and proactive maintenance practices. When applied to commercial airlines in the 1970s, RCM reduced equipment-related crashes from 40 to 0.3 per million take-offs.
How often does your team make reliability predictions?
The easy answer is very often. Each time you want to know how long a product will operate. The accompanying question on how well the estimate will match actual performance makes the real answer more difficult.
We regularly and intuitively do reliability predictions all the time. When starting a car at the beginning of a trip, we estimate the ability of the vehicle to complete the journey. When we purchase a phone, we expect it to operate for at least two years (your expectations may differ).
During the design process we may have formal or informal useful life expectations. It is not knowing if our decisions related to the design will fulfill the lifetime expectations that leads to the desire to know how well the resulting system will operate. We also may need to estimate warranty or maintenance costs, thus knowing what is likely to fail become important.
The document discusses methodology for maintenance, specifically preventive maintenance. It describes four main functions of maintenance as maintaining, keeping in existing condition, preserving, and protecting from failure or decline. Preventive maintenance is classified as either corrective or preventive. Preventive maintenance aims to prevent or mitigate failures from occurring and can be time-directed, condition-directed, or failure-finding. The document also discusses reliability centered maintenance and its features, including preserving system function over equipment. It outlines the seven-step methodology for implementing reliability centered maintenance on systems.
1. The document discusses the Measure phase of the DMAIC process for Six Sigma innovation projects.
2. Key aspects of the Measure phase include selecting Critical to Quality characteristics, defining performance standards and specifications, establishing a data collection plan, and validating measurement systems.
3. Tools discussed that are useful for the Measure phase include process mapping, fishbone diagrams, Pareto analysis, and Failure Mode and Effects Analysis (FMEA). FMEA involves identifying failure modes, causes, and effects to determine appropriate actions.
This whitepaper discusses using advanced data management and predictive analytics to improve transmission and distribution asset management. It describes how utilities can leverage non-intrusive field testing and online monitoring methods along with asset criticality, health, and risk analysis. This allows for predictive, top-down and bottom-up asset management strategies. The whitepaper argues that embracing big data analytics and predictive modeling can transform asset management from being condition-based to risk-based. This enables more informed, real-time decision making through scalable situational awareness.
This complete presentation has a set of thirty two slides to show your mastery of the subject. Use this ready-made PowerPoint presentation to present before your internal teams or the audience. All presentation designs in this Risk Analysis PowerPoint Presentation Slides have been crafted by our team of expert PowerPoint designers using the best of PPT templates, images, data-driven graphs and vector icons. The content has been well-researched by our team of business researchers. The biggest advantage of downloading this deck is that it is fully editable in PowerPoint. You can change the colors, font and text without any hassle to suit your business needs.
This document provides an overview of risk analysis. It defines key terms like risk, risk analysis, risk assessment, and risk management. It describes various qualitative and quantitative methods used for risk analysis, including hazard and operability studies, fault tree analysis, failure mode and effects analysis. The document discusses the importance of risk analysis for chemical processes and highlights some historical accidents to emphasize this. It also provides examples of applying different risk analysis methods.
The document discusses various quality management tools used for corrective and preventative action (CAPA), including root cause analysis. It defines CAPA and explains that it is required to eliminate existing nonconformities and prevent their recurrence. Various regulatory guidance on CAPA is referenced. Tools for root cause analysis discussed include the five whys technique, fishbone diagrams, Pareto charts, and fault tree analysis. Steps for conducting the five whys technique and creating fishbone diagrams are outlined. Advantages and limitations of fishbone diagrams and Pareto charts are also summarized.
This document provides an evaluation of preventative technologies for Kangaroo Inc., a dental software company. It identifies the top risks as patching, outdated firewalls, BYOD, backup failures, and lack of change control. A failure modes and effects analysis identifies patching as a major risk due to staff turnover and system diversity. The outdated firewall lacks vendor support and regional offices have expired intrusion detection. Recommendations are provided to reduce residual risks through improved patching, new firewalls, BYOD policies, backup solutions, and change control procedures.
A CAPA (Corrective and Preventive Action plan) is written to address problems identified in clinical research studies. It outlines the root cause of the problem, corrective actions taken to resolve the issue, and preventive measures to avoid future occurrences. The CAPA should be authored by the responsible party, focus on solutions rather than blame, and include a root cause analysis, corrective actions, and preventive actions. It follows a specific template that provides the issue, analyses, resolutions and plans for evaluation. The completed CAPA is submitted to the IRB and site monitors to document handling of issues.
The document discusses how to specify requirements for critical systems based on risk analysis. It explains how to identify risks, analyze and classify them, then derive safety, security, and reliability requirements to reduce risks. For reliability, it describes metrics like probability of failure on demand and mean time to failure that can be used to specify quantitative reliability levels. The goal is to develop requirements that eliminate intolerable risks and minimize other risks given cost and schedule constraints.
Corrective and Preventative Action (CAPA) is a system of quality procedures required to eliminate the causes of an existing nonconformity and to prevent recurrence of nonconforming product, processes, and other quality problems.
eCompliance, Cameron Freese_Measuring and Communicating Safety PerformanceeCompliance
Performance can be measured in many ways, but the
choice of which metrics and how to communicate these
effectively across the organization, play an important
role in establishing a strong safety culture and overall
management system. Explore how Aecon uses leading
and lagging indicators across their business to identify
themes or trends and take action.
The document discusses Failure Mode and Effects Analysis (FMEA), a systematic method for evaluating processes and identifying risks and failures. It describes the FMEA steps which include selecting a process, assembling a team, identifying potential failures and causes, analyzing severity, occurrence, detection and calculating a risk priority number. The document also notes some limitations and reasons FMEAs may fail, such as not involving all team members or getting bogged down in details.
Reducing Product Development Risk with Reliability Engineering MethodsWilde Analysis Ltd.
Overview of how reliability engineering methodology and software tools can help companies manage risk during product development and improve performance.
Presented at the Interplas'2011 exhibition and conference at the NEC on 27th October 2011 by Mike McCarthy.
This presentation looks at how ‘Reliability Engineering’ tools and methods are used to reduce risk in a typical product development lifecycle involving both plastic and metallic components. These tools range in complexity from simple approaches to managing product reliability data to the application of sophisticated simulation methods on large systems with complex duty cycles. Three examples are:
- Failure Mode Effects (and Criticality) Analysis (FMECA) to identify, manage and reuse information on what could go wrong with a design or manufacturing process and how to avoid it
- Design of Experiments for optimising performance through a structured and efficient study of parameters that affect the product or manufacturing process (e.g. injection moulding)
- Accelerated Life Testing to identify potential long term failure modes of products released to market within a shortened development time.
We will explore how gathering enough of the right kind of data and applying it in an intelligent way can reduce risk, not only in plastic product design and manufacture, but also in managing the associated supply chain and in the ‘Whole Life Management’ of products (including warranties). Furthermore, we will show how ‘sparse’ data gathered from previous or similar products, such as field/warranty reports, engineering testing data and supplier data sheets, as well as FEA, CFD and injection moulding/extrusion simulation, can inform and positively influence new product design processes from concept stage onwards.
This presentation explores the challenges, opportunities and available tools in developing a safety case regime for operators of major hazardous installations.
An analyst's perspective on measuring safety performance, discussing reactive and proactive indicators, ideas on developing proactive indicators, and a balanced scorecard approach to safety metrics
How to Measure the Relevance and Accuracy of OHS Informationdanieljohn810
This document discusses how to measure the accuracy and relevance of occupational health and safety (OHS) information. It explains that information must be reliable, valid, current and complete to be accurate. Several common OHS performance measures are examined, including safety meetings held, audits completed, and exposures exceeding standards. However, the document notes that the validity and reliability of these measures depends on clearly defining what is being measured, the data collection method, and the link to actual OHS performance. Factors like sample size, measurement protocols, and criteria for things like "close out" need consideration. The source and currency of information also impact accuracy and relevance.
This document discusses hazard analysis and risk assessment. It defines hazard and risk, and outlines the main steps in hazard analysis and risk assessment. These include identifying hazards, determining who may be harmed and how, assessing dose-response and exposure, risk management and control. Hazard analysis techniques include checklists, safety audits, preliminary hazard analysis, failure modes and effects analysis, what-if analysis, and hazard and operability studies. Risk assessment involves quantifying risk based on probability and severity. The document emphasizes that hazard analysis and risk assessment should be ongoing processes throughout the lifecycle of a system.
rrelic has developed a highly effective Total Reliability Framework for the implementation of reliability methods, tools and services in order to achieve your desired end results.
Total reliability Framework (TRF) Provides a management system for all reliability and Maintenance activities; focus on improving the performance of both the personnel and the plant equipment.
Reliability Centered Maintenance (RCM) is a process that determines the best policies for managing asset functions and failures. It considers all asset management options like condition monitoring, scheduled restoration, and scheduled discard. RCM provides the optimal mix of reactive, time-based, condition-based, and proactive maintenance practices. When applied to commercial airlines in the 1970s, RCM reduced equipment-related crashes from 40 to 0.3 per million take-offs.
How often does your team make reliability predictions?
The easy answer is very often. Each time you want to know how long a product will operate. The accompanying question on how well the estimate will match actual performance makes the real answer more difficult.
We regularly and intuitively do reliability predictions all the time. When starting a car at the beginning of a trip, we estimate the ability of the vehicle to complete the journey. When we purchase a phone, we expect it to operate for at least two years (your expectations may differ).
During the design process we may have formal or informal useful life expectations. It is not knowing if our decisions related to the design will fulfill the lifetime expectations that leads to the desire to know how well the resulting system will operate. We also may need to estimate warranty or maintenance costs, thus knowing what is likely to fail become important.
The document discusses methodology for maintenance, specifically preventive maintenance. It describes four main functions of maintenance as maintaining, keeping in existing condition, preserving, and protecting from failure or decline. Preventive maintenance is classified as either corrective or preventive. Preventive maintenance aims to prevent or mitigate failures from occurring and can be time-directed, condition-directed, or failure-finding. The document also discusses reliability centered maintenance and its features, including preserving system function over equipment. It outlines the seven-step methodology for implementing reliability centered maintenance on systems.
1. The document discusses the Measure phase of the DMAIC process for Six Sigma innovation projects.
2. Key aspects of the Measure phase include selecting Critical to Quality characteristics, defining performance standards and specifications, establishing a data collection plan, and validating measurement systems.
3. Tools discussed that are useful for the Measure phase include process mapping, fishbone diagrams, Pareto analysis, and Failure Mode and Effects Analysis (FMEA). FMEA involves identifying failure modes, causes, and effects to determine appropriate actions.
This whitepaper discusses using advanced data management and predictive analytics to improve transmission and distribution asset management. It describes how utilities can leverage non-intrusive field testing and online monitoring methods along with asset criticality, health, and risk analysis. This allows for predictive, top-down and bottom-up asset management strategies. The whitepaper argues that embracing big data analytics and predictive modeling can transform asset management from being condition-based to risk-based. This enables more informed, real-time decision making through scalable situational awareness.
Robustness validation provides a more pragmatic approach to product validation than traditional qualification methods. It seeks to define the guard band between specification limits and actual product performance to demonstrate a component's ability to withstand various stresses. The key aspects of robustness validation include understanding use conditions, failure mechanisms, developing acceleration models for testing, and testing parts until failure to determine end of life. Robustness validation results in a product qualified as "fit for application" rather than just "fit for standard" and requires more communication between customer and supplier.
Arrelic end-to-end Reliability Management allows you to;
Identify and rectify equipment problems before they happen, Reduce maintenance costs and unplanned downtime.
RCM is used to develop scheduled maintenance plans in an efficient and cost-effective manner that will provide an acceptable level of operability and risk. It focuses on processes and systems to reduce the overall cost to maintain and operate assets. Arrelic Consulting assists industries in integrating assets and increasing return on investment by enhanced asset performance and reliability.
Maintenance strategy development and optimisation through Critical Asset Ranking, RCM Approach and cost benefit analysis ensures you the best maintenance plan.
IRJET- Overview of Forecasting TechniquesIRJET Journal
This document provides an overview of different forecasting techniques, including qualitative and quantitative methods. It discusses several qualitative techniques like the Delphi method, consumer market surveys, and jury of executive opinion. It also examines various quantitative techniques such as the moving average method, weighted moving average method, exponential smoothing, and least squares. The document serves to introduce students to common forecasting approaches and provide examples of each type of technique.
- The document discusses issues with current commercial practices in process control engineering and lack of agreement on how to measure the value and performance of control systems.
- It argues that the primary purpose of process control should be to maximize expected net present value profit (ENPVP) and that Clifftent, a quantitative risk management method, provides a rigorous way to measure the financial value of dynamic performance and improved control.
- Using Clifftent, the value of process control comes from three sources: optimizing setpoints, reducing dynamic variance at a setpoint, and further optimizing setpoints for the reduced-variance situation, taking into account penalties for violating process limits.
IRJET- Maintenance and Reliability Strategy of Mechanical Equipment in IndustryIRJET Journal
This document discusses maintenance and reliability strategies for mechanical equipment in industry. It describes four main strategies: run-to-failure, preventive maintenance, predictive maintenance, and reliability-centered maintenance. Preventive maintenance involves periodically inspecting and repairing equipment on a predetermined schedule. Predictive maintenance uses data from sensors to predict failures before they occur. Reliability-centered maintenance analyzes all possible failure modes for each piece of equipment to customize maintenance plans. The strategies are compared in terms of pros, cons, and cost to implement. Reliability-centered maintenance provides the most efficient maintenance schedule but requires the most resources to execute properly.
This document is a risk assessment report that contains several sections analyzing approaches to risk assessment for an organization's IT architecture. It discusses evaluating risk, qualitative and quantitative approaches, the organization's departments and how they interconnect, security certifications, and tools for conducting risk management research such as the Plus, Minus, Interesting method and applying the "what if" approach. The report provides an in-depth analysis of how to properly assess and manage risks to an organization's IT systems.
The document proposes an integrated risk assessment process that is robust, transparent, and based on COSO and Six Sigma frameworks. It involves using a Risk and Frequency Matrix to assess risks at the process level and validate resource allocation. A Risk Profile Analysis further examines inherent, business, and technology risks. Control assessments are also made. Cause and Effect Matrices are used to link key risks to process functions. Failure Mode and Effects Analyses identify potential process weaknesses. Preventive and detective controls are categorized by type and sub-type. The process aims to identify, prioritize, and reduce risks across the organization.
Using Predictive Analytics to Optimize Asset Maintenance in the Utilities Ind...Cognizant
Predictive analytics is a process of using statistical and data mining techniques to analyze historic and current data sets, create rules and predict future events. This paper outlines a game plan for effective implementation of predictive analytics.
Devising an ideal building maintenance strateg1 https://clevair.io/Clevair
We keep living and work facilities streamlined, comfortable and maximum-productive by integrating, maintaining and installing top quality building management systems (BMS). Our BMS solutions improve the performance of building systems, increase energy efficiency while reducing maintenance costs.
https://clevair.io/blog/devising-an-ideal-building-maintenance-strategy-predictive-maintenance-vs-reactive-maintenance/
This document discusses using consequences to influence safe behavior in the workplace. It argues that behavior is primarily driven by expectations of consequences, not just training. To maximize safety performance, organizations should:
1. Measure inputs that lower risk, not just outcomes like accidents. This provides better feedback to motivate improved behavior.
2. Use positive reinforcement to drive safer behaviors by linking performance to consequences.
3. Ensure all individuals and teams are accountable for safety to eliminate weak links across the organization.
Measuring the right risk-lowering inputs and using consequences strategically can help organizations achieve continuous safety improvements and ultimately zero accidents.
This document discusses a Program Implementation Platform (PIP) used by energy companies to implement energy conservation programs. PIP consists of modules to manage the program from data collection to analysis. Field executives collect home data which is analyzed for consistency and quality using established limits, bounds checking, and pattern detection. This continuous quality assurance process flags anomalous data and detects potential fraud or incompetency. The PIP system helps energy company CIOs focus on objectives, detect fraud, and ensure consistent home ratings through automated data analysis and silent fraud detection features. Addressing issues like training helps address incompetency concerns.
The document provides an overview of failure mode and effects analysis (FMEA). It defines FMEA as a systematic technique used to evaluate potential failures and their causes. The objective is to classify possible failures by their severity, occurrence, and detection to find solutions that eliminate or minimize risks. The document outlines the FMEA process, which involves determining the process/component, identifying potential failure modes and effects, rating severity, occurrence, and detection, calculating the risk priority number, and planning corrective actions. FMEA is a proactive method used in design, manufacturing, and other stages to prevent defects and improve quality.
This document discusses data, variation, and process capability. It defines two types of data: continuous data which can be measured, and discrete data which can only be observed and counted. It also explains how to measure the location and spread of data using statistics like the mean, median, mode, standard deviation, and range. The document distinguishes between chance variation from random causes and assignable variation from non-random causes. It states that a process is considered statistically controlled when it only exhibits chance variation. Finally, it defines process capability as representing a process's best performance when under statistical control, and describes different indices used to measure potential capability and demonstrated excellence.
The document discusses the conduct of operations at a nuclear power plant. It states that conduct of operations establishes operating principles and a control system to support a culture of safety and disciplined professionals. It aims to continuously improve operational performance through goals like minimizing safety system unavailability and personnel errors. Key tools for conduct of operations include quality and consistent training, safety policies, communications, procedures, and emphasizing that personnel and nuclear safety take priority over power production.
For many manufacturers, evaluating and managing the risk of obsolescence is a missing piece of their overall management strategy, an oversight that can have significant implications in terms of business continuity. With a clear obsolescence policy and risk-assessment framework, manufacturing companies can help ensure that their systems and assets remain up and running, supported by a continuous risk-mitigation cycle.
Condition-based Maintenance with sensor arrays and telematicsGopalakrishna Palem
Emergence of uniquely addressable embeddable devices has raised bar on Telematics capabilities. Sensor based Telematics technologies generate volumes of data that are orders of magnitude larger than what operators have dealt with previously. Real-time big data architectures enable real-time control and monitoring of data to detect anomalies and take preventive action. Condition-based-maintenance, usage-based-insurance, smart metering and demand-based load generation are some of the predictive analytics use cases for Telematics with real-time data streaming. This paper presents indepth analysis of condition-based maintenance using real-time sensor monitoring, Telematics and predictive data analytics.
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
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1. Transmission & Distribution August/September 20161
T&D
I
n today’s networks many utilities have some level of condition
monitoring. It may be as simple as visual inspections, regular testing,
sampling or it could be more mature with a great deal of on-line and
off-line data being captured. No matter what the level there are some
underlying facts that often get over looked.
RESULT IN SIGNIFICANT COSTS
The successful transmission and distribution of electrical energy is crucial
in our everyday lives and underpins virtually everything we do in the
world. Customers expect their electricity to be safely distributed and
highly reliable. Outages only cause relatively minor inconveniences for
household users, but can result in significant costs to businesses or
causing disruptions to thousands of people. These outages usually occur
as a result of equipment failures within the transmission or distribution
network. Substation equipment such as transformers are the major part
of any network, and failures often result in long unplanned outages.
Ideally, every item of plant in the network should be assessed in detail to
correctlyestimatewhenandhowafailuremightoccur.Ifthisinformation
is obtained, the equipment could either undergo maintenance or be
replaced depending on the cost and likelihood of the failure. Although
an outage might be needed when doing this, it can be planned, loads
transferred without disruption or providing customers with sufficient
notice of the outage. Furthermore, the outage time and associated cost
of failures can be greatly reduced.
When considering the two points in the blue box above and looking
at comparing the options of continuous monitoring and discrete
monitoring, you must balance the cost of monitoring against the cost of
failures missed and cost of false alarms. Continuous on-line monitoring
can appear to be expensive but it is less likely to miss a failure, however
it does give more false alarms.
COST OF THE SAMPLING INTERVAL
For periodic monitoring you must balance the cost of the sampling
interval against the cost of missed failures. This balance is not easy to
achieve. The more devices and techniques used to monitor equipment
means the amount of data being obtained increases and so more
analysis is required. Also, it is easy to obtain volumes of data but it
is more difficult to turn that data into information that can be used
for decision making. To show an example, consider the following two
simple methods of condition monitoring of the insulation system of a
power transformer:
i DGA analysis has almost zero level of false alarms if samples are
taken and tested correctly. Depending on frequency of sampling
– yearly, bi-yearly, etc. - there could and almost certainly will be a
number of failures missed.
ii DLA analysis. As the partial breakdown progresses, the electrical
properties of the insulation change and it has higher losses. Since
there are a number of factors that affect the power factor and
it is a measurement of the total insulation system, it is not easy
to identify the cause of a bad result nor is it good at detecting
localised faults.
It should also be noted here that in most cases an oil sample may be
taken whilst the transformer is still in service, however, the DLA test
can only be performed with the transformer totally disconnected.
Therefore, the availability and cost of the outage needs to also be
considered with both method and frequency of sampling.
RISK AND CONDITION BASED MANAGEMENT METHOD
If we look at using risk as the method of deciding what condition
monitoring should be done then fundamentally no calculations are
needed, or is that right? The simple thing to do is just analyse the risk
from a high level point of view. Different monitoring systems reduce the
risk to a different extent, so why not just look at each technique and
weigh up the risk of not detecting a fault against the consequence of
the fault. This sounds too easy but one must consider the effectiveness
of reducing the risk by looking at the cost of using the technique and
the level of risk reduction. The equipment being monitored also needs
to be given a risk value which considers the type of equipment, its cost,
criticality to the network and network usage.
One needs to live with the fact that it may well be considered that the
risk of failure of some equipment is so low that almost no monitoring is
needed apart from routine maintenance.
DETERMINING CONDITION
BASED ASSET MANAGEMENT
STRATEGIES
When considering the effectiveness of any asset condition monitoring,two key factors need to be considered:
1. The rate at which failures are missed. That is, failures that occurred and the system data and trends did
not detect it.
2. The rate at which false alarms are triggered. This is when a failure is indicated but there is no defect
actually present.
PART 1 - INTRODUCTION
Kerry Williams of K-BIK Power Pty Ltd
CONDITION MONITORING
2. Transmission & Distributionwww.powertrans.com.au 2
T&D
A number of aspects need to be considered with the risk method:
• Issue of risk of failure of the plant. Irrespective of cost, this must be
reduced to a level that can be considered tolerable.
• Cost, should a method be able to satisfy the failure risk problem,
then which is it the lowest cost?
• The risk of injury or death to personnel. This cannot be ignored
and depending on the equipment type, can have a substantial
impact on the cost.
• Risks associated with loss of supply and corporate reputation. In
some instances, these risks can drive the cost high in an effort to
ensure a utility provides reliable supply to high profile customers.
Itisherethatwenotethatmostmodernassetmanagementpracticesare
tending toward condition based maintenance but have an underlying
level of risk that is used in the assessing an item of plant to be monitored
or not. If it is assessed as low risk and not to be monitored with have a
very different impact on the maintenance strategy than plant assessed
as high risk but still in very good condition. That is, an item of plant can
be performing extremely well without any issues, yet its risk profile has
it rated very high on criticality to the network. So again just using only
a condition based assessment would not recognise the importance of
such assets. Hence, the two, condition and risk must be considered
collectively and weighted accordingly.
What about not monitoring: How can you do condition based
maintenance if you are not monitoring the condition? The answer is
simple, you can’t. There needs to be some level of monitoring to be
able to effectively assess the condition of the asset albeit every few
years. Again, the monitoring can take many forms and cover many
techniques and deliver all the data to assess. At the end of the day,
all of this presents us with a problem: How to select the most suitable
monitoring method for any asset fleet and then select the optimum
sampling period.
RIGHT TECHNIQUE FOR A PROCESS
Before any method of monitoring can be selected or considered as the
right technique for a process needs to be followed that determines the
fundamental reasons for monitoring. The diagram in Figure 1 gives
a simplistic view of the process. It starts with determining the asset
strategy requirements. What is it and why do condition monitoring or
asset management and what is it that needs to achieved. Most utilities
and companies have an asset management strategy and this can be
leveraged even if it is not up to date. The next step is to establish the
asset performance and condition standards. All organisations need
to have a level of asset performance that is acceptable to them. To
continually achieve that performance, the condition criteria need to be
set as minimum standards of acceptability. Without these there is no
organisational or industry benchmark from which to assess the asset.
This step is probably to most important of all as it sets not only the
performance criteria and what you want to measure but also needs to
determine the information needed from the data to make a decision.
Once you have the strategy and the standards of performance you can
then implement them by performing the condition assessment and
gathering all the data you decided was needed. Once gathered, the
data needs to be used to actually determine the asset condition. To
do this, the condition data gathered needs to be added to the asset
rating, criticality (risk), work needed to bring the asset to performance
levels required and finally the cost estimates for achieving the desired
performance.
At this juncture there is a need to split the risk from the condition,
so that those criteria previously mentioned in risk (safety, reputation,
criticality etc.) can be reviewed separately from the asset condition.
The asset condition needs to have specialist analysis and can be review
as a health index or other score based assessment of its condition.
From there one needs to determine the actions needed to address
the condition, this may well be “do nothing” or “total replacement”,
either way a decision must be made.
CONCLUSION
By using that determination and reviewing it with the risk profile the
assets in any network can be prioritised based on the condition and
risk. Once those priorities have been determined, it is only then that
proper planning to perform the work necessary within a budget can
be undertaken.
The above may seem a very simple and normal approach to condition
based asset management strategies, however, I would challenge you
to look closely at your organisations methods and methodically step
through the process. Quite often many areas work very well, but just as
often many areas fall short of the desired outcomes. I will delve into a
few of these areas in the next article in this short series.
Determine Asset
Strategy
Requirements
Establish Asset
Performance &
Condition
Standards
Perform
Condition
Assessment
Determine Asset
Condition
Rating & Criticality
Work Estimates
Determine Risks
associated with
Condition
Likelihood
Consequence
Develop Asset
Condition
Database &
Analysis
Determine Actions
Needed on Asset
Set asset
Priority
based on
Condition
& Risk
Plan & Perform
Work
Field Feedback
Figure 1 - A Typical Asset Management Process
Using Condition Monitoring and Risk Evaluations
Figure 1 A Typical Asset Management Process Using Condition Monitoring and Risk Evaluations
K-BIK Power
PO Box 3204, Darra QLD 4076
M +61 (0)409 582 263
T +61 (07) 3160 1082
E Kerry.Williams@kbikpower.com.au