Support poster for the paper "Resilient Bioinspired Algorithms: A Computer System Design Perspective", presented at EvoStar 2022, https://doi.org/10.1007/978-3-031-02462-7_39
A Decision Support System Based on RCM Approach to Define Maintenance StrategiesCONFENIS 2012
The document proposes a decision support system (DSS) to help define maintenance strategies based on reliability centered maintenance (RCM) principles. The DSS has two modules: a physical module describing production system components, and a functional module using failure analysis and criticality assessment to recommend strategies like scheduled maintenance, discard/redesign, or condition-based maintenance. The DSS provides a logical process for defining customized strategies while considering factors like costs, quality, and production performance. Multicriteria decision methods can also influence the analysis and definition of maintenance actions. The DSS is intended to support operations management and recommend strategic activities grounded in decision theory.
This document discusses quality attributes that are important considerations for software architects. It defines key attributes like availability, modifiability, performance, security, and testability. It presents these attributes as general scenarios to help stakeholders communicate and understand them. The document also covers business qualities and architectural qualities that influence design decisions.
Testability refers to the design parameter which makes it relatively easy to identify and isolate faults in the system. Testability can be considered to be a subset of maintainability, because fault detection and isolation are important drivers in the maintainability of a system
Implementing effective preventive and predictive maintenance programshossam hassanein
The document discusses implementing effective preventive and predictive maintenance programs. It covers various maintenance strategies including reactive, preventive, predictive, reliability-centered, and total productive maintenance. Key aspects of developing a preventive maintenance program are discussed such as performing a feasibility analysis, establishing time-based or dynamic-based schedules, and calculating overall equipment effectiveness. The document provides an overview of setting up an effective maintenance program.
Embedded Systems (18EC62) – Embedded System Design Concepts (Module 4)Shrishail Bhat
This document discusses the characteristics and quality attributes of embedded systems. It describes several key characteristics of embedded systems, including being application specific, reactive and operating in real time, able to function in harsh environments, potentially distributed across multiple components, and having constraints on size, weight and power consumption. The document also distinguishes between operational quality attributes, like response time, throughput, reliability and maintainability, and non-operational attributes such as testability, evolvability and portability. Maintainability and reliability are discussed in detail through examples of mean time between failures and mean time to repair calculations.
This document discusses reliability-centered maintenance (RCM). It defines RCM as a corporate maintenance strategy that aims to optimize maintenance programs by preserving system functions through identifying failure modes and selecting effective tasks to control failures. The document outlines the history and principles of RCM, describing the classical and streamlined approaches. It provides an overview of the basic RCM process, which involves preparation, analysis, task selection, comparison, and record keeping. The advantages of RCM include lowering costs and minimizing failures, while disadvantages include startup costs and challenges dealing with hidden failures.
This document discusses reliability-centered maintenance (RCM). It defines RCM as a corporate maintenance strategy that aims to optimize maintenance programs by preserving system functions through identifying failure modes and selecting effective tasks to control failures. The document outlines the history and principles of RCM, describing the classical and streamlined approaches. It provides an overview of the basic RCM process, which involves preparation, analysis, task selection, comparison, and record keeping. The advantages of RCM include lowering costs and minimizing unexpected failures, while disadvantages include initial costs and challenges dealing with hidden failures.
A Decision Support System Based on RCM Approach to Define Maintenance StrategiesCONFENIS 2012
The document proposes a decision support system (DSS) to help define maintenance strategies based on reliability centered maintenance (RCM) principles. The DSS has two modules: a physical module describing production system components, and a functional module using failure analysis and criticality assessment to recommend strategies like scheduled maintenance, discard/redesign, or condition-based maintenance. The DSS provides a logical process for defining customized strategies while considering factors like costs, quality, and production performance. Multicriteria decision methods can also influence the analysis and definition of maintenance actions. The DSS is intended to support operations management and recommend strategic activities grounded in decision theory.
This document discusses quality attributes that are important considerations for software architects. It defines key attributes like availability, modifiability, performance, security, and testability. It presents these attributes as general scenarios to help stakeholders communicate and understand them. The document also covers business qualities and architectural qualities that influence design decisions.
Testability refers to the design parameter which makes it relatively easy to identify and isolate faults in the system. Testability can be considered to be a subset of maintainability, because fault detection and isolation are important drivers in the maintainability of a system
Implementing effective preventive and predictive maintenance programshossam hassanein
The document discusses implementing effective preventive and predictive maintenance programs. It covers various maintenance strategies including reactive, preventive, predictive, reliability-centered, and total productive maintenance. Key aspects of developing a preventive maintenance program are discussed such as performing a feasibility analysis, establishing time-based or dynamic-based schedules, and calculating overall equipment effectiveness. The document provides an overview of setting up an effective maintenance program.
Embedded Systems (18EC62) – Embedded System Design Concepts (Module 4)Shrishail Bhat
This document discusses the characteristics and quality attributes of embedded systems. It describes several key characteristics of embedded systems, including being application specific, reactive and operating in real time, able to function in harsh environments, potentially distributed across multiple components, and having constraints on size, weight and power consumption. The document also distinguishes between operational quality attributes, like response time, throughput, reliability and maintainability, and non-operational attributes such as testability, evolvability and portability. Maintainability and reliability are discussed in detail through examples of mean time between failures and mean time to repair calculations.
This document discusses reliability-centered maintenance (RCM). It defines RCM as a corporate maintenance strategy that aims to optimize maintenance programs by preserving system functions through identifying failure modes and selecting effective tasks to control failures. The document outlines the history and principles of RCM, describing the classical and streamlined approaches. It provides an overview of the basic RCM process, which involves preparation, analysis, task selection, comparison, and record keeping. The advantages of RCM include lowering costs and minimizing failures, while disadvantages include startup costs and challenges dealing with hidden failures.
This document discusses reliability-centered maintenance (RCM). It defines RCM as a corporate maintenance strategy that aims to optimize maintenance programs by preserving system functions through identifying failure modes and selecting effective tasks to control failures. The document outlines the history and principles of RCM, describing the classical and streamlined approaches. It provides an overview of the basic RCM process, which involves preparation, analysis, task selection, comparison, and record keeping. The advantages of RCM include lowering costs and minimizing unexpected failures, while disadvantages include initial costs and challenges dealing with hidden failures.
A powerpoint presentation on embedded systems for students and graduates.
Embedded system is an electronic or electro-mechanical system designed to perform a specific task & is combination of both hardware and software.
Every Embedded system is unique, hardware & software are highly specified to the application domain.
#education #technology #business #embeddedsystems #embedded #systems #datacollection #datacommunication #dataprocessing #monitoring #control #application #interface #content #advantages #disadvantages #bridge #electromechanical
Enhancing Capacity Utilization of Coal Fired Thermal Power Plant through Bett...Premier Publishers
This paper describes the capacity enhancement of coal fired power plants through operational optimization, control techniques and better maintenance practices. The philosophy of “Prevention is Better than Cure” is dealt in detail to improve the Plant load factor (PLF) of plant. The energy conservation measures are also implemented in improving the plant performance and are enumerated in this paper. By adopting better maintenance practices for thermal power plants, enhance the capacity utilization of plants, thereby the present average PLF of 73.3 % of 210 and 250 MW units can be enhanced to about 95 % that will release an additional energy of about 1.2 lakh MU/year.
PlantConnect – plant asset monitoring system (pams)Akshay Tilak
Plant Asset Management refers to optimally and sustainably managing assets, associated performance, risks and expenditures over their lifecycles to achieve organizational goals. An important aspect is maintenance management to ensure optimum asset performance. PlantConnect is a Plant Asset Management solution that gives machines a "voice" through continuous online monitoring of machine operations data to assess asset health and advise on maintenance. It monitors key performance indicators, manages maintenance, and enables energy monitoring to reduce costs and enhance benefits.
Regression testing is testing performed after changes to a system to detect whether new errors were introduced or old bugs have reappeared. It should be done after changes to requirements, new features added, defect fixes, or performance improvements. There are various strategies for regression testing including re-running all tests, test selection, test prioritization, and focusing on areas like frequently failing tests or recently changed code. While regression testing helps ensure system quality, managing large test suites over time can be challenging. Automating regression testing helps address these challenges.
Regression testing is testing performed after changes to a system to detect whether new errors were introduced or old bugs have reappeared. It should be done after changes to requirements, new features added, defect fixes, or performance improvements. There are various strategies for regression testing including re-running all tests, test selection, test prioritization, and focusing on areas like frequently failing tests or recently changed code. While regression testing helps ensure system quality, managing large test suites over time poses challenges in minimizing tests while achieving coverage. Automating regression testing can help address these challenges.
Following presentation answers:
- Why do we need evolution?
- What happens if we do not evolve the software?
- What are the types of software evolution?
- What are Lehman's laws
- What are the strategies for evolution?
The document discusses various types of maintenance strategies including reactive, preventive, predictive, proactive, and reliability centered maintenance. Reactive maintenance involves fixing equipment only after it breaks down while preventive maintenance relies on routine inspections and servicing at pre-determined intervals. Predictive maintenance uses condition monitoring technologies to detect potential failures in advance. Proactive maintenance seeks to eliminate the root causes of failures to improve reliability. Reliability centered maintenance combines predictive and proactive approaches along with preventive maintenance and aims to optimize equipment performance and reduce downtime.
Predictive maintenance is a process that uses monitoring technologies and big data analysis to determine the condition of equipment in order to predict when maintenance should be performed. Sensors continuously collect machine component data which is sent to the cloud for analysis. By analyzing current and historical equipment data, anomalies can be predicted and addressed through planned maintenance to minimize downtimes and repair costs compared to traditional preventive maintenance approaches. Predictive maintenance allows businesses to reduce costs, increase productivity and safety through proactive maintenance strategies enabled by industrial IoT technologies.
Maintenance involves keeping software or assets in working condition. There are four main types of maintenance: corrective, adaptive, preventive, and perfective. Maintenance is needed to fix problems, adapt to new environments, prevent issues, and improve performance. While necessary, maintenance is costly due to the work required to modify existing software. Efforts like designing for change and documentation can help reduce these costs. Overall, maintenance plays a critical role in maximizing the usefulness of software over its lifetime.
A subfield of engineering known as control engineering is concerned with the planning, development, and use of systems that govern or control other systems.
Reliability is the ability of a system or component to function under stated conditions for a specified period of time. There are several reasons why failures occur, including design flaws, overstressing, wear and tear, vibration, incorrect specifications, misuse, and operating outside intended environments. The objectives of reliability engineering are to prevent or reduce failures, identify and correct causes of failures, determine ways to cope with failures, and estimate reliability of new designs. Reliability is defined as the probability of success and avoids downtime, repair costs, and warranty claims. Modes of failure include initial infant mortality failures, random stable failures, and wear-out failures over time depicted by a bathtub curve. Reliability influences system
An intelligent maintenance system (IMS) utilizes sensors and data analysis to predict failures in machinery. It analyzes machine behavior data to provide alarms and instructions for preventive maintenance. Key aspects of IMS include transforming data into knowledge, using prognostic algorithms to assess degradation and predict performance, and employing software and hardware platforms to run online models. IMS aims to avoid costly and catastrophic machinery failures through predictive maintenance capabilities.
Are Your Process Automation Assets in Tune with Your Manufacturing Assets?ARC Advisory Group
The document discusses how effective process automation is key to operational excellence and improving return on assets (ROA) for manufacturing companies. While cost cutting has limitations, using automation to add value through more efficient use of manufacturing assets leads to higher performance. The document recommends that companies evaluate their process automation strategies to achieve precise implementation and flawless execution, institute continuous improvement programs for process automation, acquire monitoring tools to facilitate a six sigma approach, and integrate process automation performance monitoring into plant performance reporting.
Software systems must evolve over time to remain useful as requirements, environments, and technologies change. There are several processes involved in software evolution, including software maintenance to fix bugs, adapt to new environments, or implement new functionality. Legacy system evolution requires assessing the business value and quality of the system to determine the best strategy, such as continuing maintenance, reengineering to improve maintainability, or replacing the system.
The document discusses reliability in asset management and maintenance. It defines reliability as machines producing quality output at design capacity for their lifetime. It discusses moving from reactive to proactive maintenance through a culture change. Key aspects are implementing preventive, predictive, and proactive maintenance approaches and using metrics to measure inputs and outputs. Case studies demonstrate benefits of condition monitoring to avoid breakdowns.
This document discusses trends in maintenance management. It outlines several strategies for maintenance including reliability centered maintenance (RCM), total productive maintenance (TPM), total quality management (TQM), condition-based maintenance (CBM), and planned preventive maintenance. New concepts in maintenance include adopting new technologies, using mobile devices, data-driven decision making, and integrating maintenance data with other systems. The future of maintenance involves leveraging the internet of things to more proactively perform maintenance and predict asset failures.
This document discusses resilient system design and how complex systems can fail. It explains that imagined systems designed on paper differ from real-world systems due to drift over time from random events, weaknesses in design, changes, and normal variation. To improve systems, the document recommends continuously maintaining systems, revealing controls to operators, identifying leverage points, simulating failures, and developing prevention methods. It also provides examples of how these principles can be applied to production, quality, safety, and information systems.
This document discusses resilient system design and how complex systems can fail. It explains that imagined systems designed on paper differ from real-world systems due to drift over time from random events, weaknesses in design, changes, and normal variation. To improve systems, the document recommends continuously maintaining systems, revealing controls to operators, identifying leverage points, simulating failures, and developing prevention methods. It also provides examples of how these principles can be applied to production, quality, safety, and information systems.
GAMP 5 provides a framework for validating computerized systems used in regulated industries. It recommends a life cycle approach involving quality risk management throughout planning, development, validation and operation. Key activities for regulated companies include governance, identifying systems' impact, and ensuring compliance. Suppliers play an important role by providing documentation, testing systems, and supporting changes and maintenance. The level of validation should be based on a system's risk, complexity and novelty.
The document discusses critical systems where failures can have severe consequences. It defines four dimensions of dependability - availability, reliability, safety, and security. Development methods for critical systems aim to avoid mistakes, detect and remove errors, and limit damage from failures. The dependability of a system reflects how much users trust that it will operate as expected without failures.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
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Regression testing is testing performed after changes to a system to detect whether new errors were introduced or old bugs have reappeared. It should be done after changes to requirements, new features added, defect fixes, or performance improvements. There are various strategies for regression testing including re-running all tests, test selection, test prioritization, and focusing on areas like frequently failing tests or recently changed code. While regression testing helps ensure system quality, managing large test suites over time poses challenges in minimizing tests while achieving coverage. Automating regression testing can help address these challenges.
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Predictive maintenance is a process that uses monitoring technologies and big data analysis to determine the condition of equipment in order to predict when maintenance should be performed. Sensors continuously collect machine component data which is sent to the cloud for analysis. By analyzing current and historical equipment data, anomalies can be predicted and addressed through planned maintenance to minimize downtimes and repair costs compared to traditional preventive maintenance approaches. Predictive maintenance allows businesses to reduce costs, increase productivity and safety through proactive maintenance strategies enabled by industrial IoT technologies.
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Resilient Bioinspired Algorithms: A Computer System Design Perspective
1. Resilient Bioinspired Algorithms
A Computer System Design Perspective
C. CottaUMA, ITIS, G. OlagueCICESE
The normal operation of the
system should not result in
damage in its own state
Diversity loss
Premature convergence
Malicious agents
The system can perform changes on itself
or adapt any aspect of its functioning in
order to ensure appropriate performance
• Self-tuning
• Meta-optimization
The system must perform above specific
functioning requirements, and deliver
correct service conditions beyond the
typical domain of operation
Fault tolerance
Repairability
Intrinsic
Extrinsic
Self-healing
The system must provide
continuous service and
maximize its readiness to it.
• Service continuation in the presence of failures
• Service continuation in changing environments
Dynamic
optimization
The system must maintain
its operation in the long run.
Green AI
Sustainability
Systems with a low systemic risk build-up increasingly
fragile, ultimately undermining sustainability
Volatility Paradox
Resilience is an intrinsic feature of bioinspired
optimization techniques that deserves further analysis.
Resilience should be boosted to improve the
performance and usefulness of bioinspired optimization
techniques.
Position
Population(s)
Algorithmic add-ons,
checkpointing