Use Cases Automotive Asset Health Management (AHM)

Asset Health Management (AHM)

Asset Health Management refers to the process of analyzing the health of an asset as determined by operational requirements. The health of an asset in itself relates to the asset's utility, its need to be replaced, and its need for maintenance. It can be broken down into three key components: 1) Monitoring: Tracking the current operating status of the asset. 2) Diagnostic Analysis: Comparing real-time data to historical data in order to detect anomalies. 3) Prognostic Analysis: Identifying and prioritizing specific actions to maximize the remaining useful life of the asset based on analysis of real-time and historical data.

Read More
Remote Gas Pipeline Tunnel Temperature Monitoring System
Remote Gas Pipeline Tunnel Temperature Monitoring System
One of Singapore's leading engineering and system integration providers needed exactly the right solution for a challenging gas pipeline application. With experience in assembling systems for many different vertical markets such as oil and gas networks, factory automation, and building automation, this system integrator realized that monitoring the temperature of a gas pipeline tunnel is crucial for safe operations. In the confined space of a tunnel, temperature rises easily, and the overheating could cause pipeline fractures that could lead to gas leaks or even explosions. Meanwhile, the long and narrow dimensions inherent to a tunnel meant that more home run cables must be installed to link all the temperature gauge data acquisition I/O devices back to the pipeline's SCADA system, increasing cabling costs. With these stakes and in these conditions, the simple act of regularly taking the temperature transforms into a formidable yet absolutely necessary requirement. System Requirements • Real-time tunnel temperature monitoring to provide early excessive heat warnings • Data acquisition and system management with SCADA system • Ethernet data acquisition system, but with efficient, cost-effective wiring
Connected Transportation: A Smarter Brain for Your Train with Intel
Connected Transportation: A Smarter Brain for Your Train with Intel
A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.
Best Buy Slashes App Development Time And Resources With Xively (GCP App)
Best Buy Slashes App Development Time And Resources With Xively (GCP App)
Best Buy wanted to quickly develop and deploy apps to achieve business goals. Also, create apps that are scalable and low-maintenance.

From 2013 to 2022, the market for overall asset efficiency improvements potentially accumulates to USD 2.5 trillion.

Source: Cisco

What is the business value of this IoT use case and how is it measured?
Your Answer

1. Proactive Maintenance and Downtime Reduction: AHM enables organizations to shift from reactive to proactive maintenance practices, significantly reducing unplanned downtime and associated costs. By continuously monitoring asset health indicators in real-time, organizations can detect potential issues early, schedule preventive maintenance activities, and address emerging problems before they escalate into costly failures.

2. Optimized Asset Performance and Reliability: AHM systems provide valuable insights into asset condition, performance trends, and failure modes, allowing organizations to optimize asset performance and reliability. By analyzing historical data, identifying performance patterns, and applying predictive analytics, organizations can optimize asset utilization, extend asset lifespan, and enhance overall operational efficiency.

3. Data-Driven Decision Making and Resource Allocation: Leveraging data analytics and predictive maintenance capabilities, AHM enables organizations to make data-driven decisions about asset management strategies, resource allocation, and investment prioritization. By analyzing asset health data, organizations can identify high-risk assets, allocate resources more effectively, and optimize maintenance schedules to maximize asset availability and minimize operational risks.

4. Compliance and Regulatory Adherence: AHM solutions help organizations maintain compliance with regulatory requirements, industry standards, and performance metrics governing asset integrity and safety. By implementing robust asset health monitoring systems and documentation practices, organizations can demonstrate compliance with regulatory mandates, mitigate legal and regulatory risks, and uphold industry best practices to maintain stakeholder trust and confidence.

5. Enhanced Business Resilience and Competitiveness: Effective asset health management enhances organizational resilience and competitiveness by minimizing downtime, optimizing asset performance, and reducing operational risks. Organizations that adopt AHM solutions gain a competitive edge by improving operational efficiency, reducing costs, and delivering superior products and services to customers. By investing in AHM capabilities, organizations can position themselves for long-term success and sustainability in dynamic and competitive markets.

Who is involved in purchasing decisions, and who are the primary system users?
Your Answer

1. Asset Owners and Operators: Asset owners and operators are directly responsible for managing and maintaining assets throughout their lifecycle. Their primary concern is maximizing asset performance, reliability, and lifespan while minimizing operational risks and costs. Asset owners rely on AHM systems to provide real-time insights into asset health, enabling proactive maintenance, optimizing asset utilization, and ensuring compliance with regulatory requirements. They seek AHM solutions that offer comprehensive asset monitoring, predictive analytics, and actionable insights to support data-driven decision-making and enhance overall asset management practices.

2. Maintenance and Reliability Teams: Maintenance and reliability teams are tasked with executing maintenance activities, optimizing asset performance, and minimizing downtime. Their viewpoint emphasizes the importance of AHM in streamlining maintenance workflows, prioritizing maintenance tasks, and identifying potential issues before they escalate into costly failures. Maintenance teams require AHM solutions that integrate with existing maintenance management systems, provide predictive maintenance capabilities, and facilitate collaboration and communication among team members. They seek AHM tools that empower them to proactively manage asset health, optimize maintenance schedules, and improve overall asset reliability and uptime.

3. Asset Management Professionals: Asset management professionals oversee strategic asset planning, investment decisions, and risk management initiatives. Their viewpoint focuses on leveraging AHM to support long-term asset planning, optimize asset lifecycle costs, and align asset management strategies with organizational goals and objectives. Asset management professionals require AHM solutions that provide comprehensive asset performance data, support lifecycle cost analysis, and enable scenario planning and decision modeling. They seek AHM tools that facilitate strategic asset planning, enhance risk mitigation strategies, and enable continuous improvement in asset management practices.

4. Regulatory Authorities and Compliance Agencies: Regulatory authorities and compliance agencies establish regulations, standards, and guidelines governing asset integrity, safety, and reliability. Their viewpoint emphasizes the importance of AHM in ensuring compliance with regulatory requirements, mitigating operational risks, and maintaining asset integrity. Regulatory authorities require AHM solutions that provide transparent reporting, audit trails, and documentation capabilities to demonstrate compliance with regulatory mandates. They seek AHM tools that facilitate regulatory compliance, support data integrity and security, and enable organizations to uphold industry best practices and standards.

Which technologies are used in a system and what are the critical technology?
Your Answer

1. Sensor Technology and IoT Devices: Sensor technology and Internet of Things (IoT) devices serve as the foundation of AHM, providing real-time data on asset condition, performance, and health. Stakeholders must evaluate sensor technologies for their accuracy, reliability, and compatibility with asset types and operating environments. Investing in advanced sensors with capabilities such as vibration analysis, temperature monitoring, and corrosion detection enables stakeholders to capture comprehensive asset health data and detect early warning signs of potential failures.

2. Data Analytics and Predictive Maintenance: Data analytics and predictive maintenance algorithms empower stakeholders to extract actionable insights from asset health data, predict asset failures, and optimize maintenance strategies. Leveraging machine learning, artificial intelligence, and statistical modeling techniques enables stakeholders to analyze historical data, identify patterns, and forecast future asset performance. Implementing predictive maintenance solutions that integrate with asset management systems and provide real-time alerts helps stakeholders proactively address asset issues and minimize downtime.

3. Cloud Computing and Edge Computing: Cloud computing and edge computing technologies offer scalable and flexible platforms for storing, processing, and analyzing large volumes of asset health data. Cloud-based AHM platforms provide stakeholders with centralized access to real-time data, analytics tools, and collaboration capabilities, enabling seamless data sharing and decision-making across the organization. Edge computing solutions enhance AHM by enabling real-time data processing and analysis at the edge of the network, reducing latency and enabling timely response to asset health events in remote or bandwidth-constrained environments.

What data is obtained by the system and what are the critical data management decision points?
Your Answer

1. Data Acquisition and Integration: Effective AHM relies on the seamless acquisition and integration of data from various sources, including sensors, monitoring devices, maintenance logs, and operational systems. Stakeholders must ensure interoperability and compatibility between different data sources and formats to enable comprehensive asset monitoring and analysis. Implementing standardized data acquisition protocols and leveraging integration platforms facilitate the seamless flow of data across the organization, enabling stakeholders to access timely and accurate information about asset health and performance.

2. Data Quality and Integrity: The quality and integrity of data are paramount in AHM, as decisions and actions are based on the insights derived from data analysis. Stakeholders must implement robust data quality assurance measures to ensure that data is accurate, reliable, and trustworthy. Data validation techniques, error detection algorithms, and outlier detection mechanisms help identify and rectify data anomalies, inconsistencies, and errors, ensuring the integrity of asset health data and enhancing the reliability of predictive analytics and decision-making processes.

3. Advanced Analytics and Predictive Modeling: Leveraging advanced analytics and predictive modeling techniques enables stakeholders to extract actionable insights from asset health data, identify patterns, and forecast potential failures. Machine learning algorithms, statistical models, and predictive analytics tools analyze historical data, detect emerging trends, and generate predictive maintenance alerts, enabling stakeholders to proactively address asset issues and optimize maintenance strategies. Implementing scalable analytics platforms and investing in data science capabilities empower stakeholders to unlock the full potential of asset health data and drive continuous improvement in AHM practices.

What business, integration, or regulatory challenges could impact deployment?
Your Answer

1. Data Integration and Interoperability: Integrating data from disparate sources, such as sensors, equipment, and maintenance systems, poses a significant challenge in AHM deployment. Different data formats, standards, and protocols hinder seamless data integration, leading to data silos and interoperability issues. Overcoming data integration challenges requires implementing robust data integration platforms, standardized data formats, and interoperability protocols to facilitate the seamless flow of data across the organization.

2. Legacy Infrastructure and Technology: Many organizations face challenges in deploying AHM solutions due to legacy infrastructure and outdated technology systems. Legacy equipment, software, and communication protocols may lack compatibility with modern AHM technologies, impeding deployment efforts. Upgrading legacy infrastructure, retrofitting existing assets with sensors, and integrating legacy systems with new AHM solutions require careful planning, investment, and technical expertise to ensure compatibility and seamless operation.

3. Change Management and Organizational Culture: Implementing AHM initiatives often requires changes in organizational culture, processes, and workflows. Resistance to change, lack of awareness, and cultural barriers hinder AHM adoption and deployment efforts. Overcoming change management challenges requires proactive communication, stakeholder engagement, and training programs to educate employees, foster buy-in, and promote a culture of continuous improvement and innovation.

Erik Walenza-Slabe
Download PDF Version
test test