Achieving Asset Performance Excellence for Industry 4.0
Managing Asset Performance in Manufacturing
One of the most important decisions that an asset-intensive enterprise must make is how to manage and care for its assets. Assets can include equipment, buildings, plants and individual machines. This is a decision that affects everyone in the organization, from the plant operators to the engineers and all the way to executives in the C-suite. The solution will be different depending on the needs of the business and how each uses its assets.
For the manufacturing industry, in which machines are directly related to the delivery of the end product, the aim must be to implement solutions that ensure and improve the reliability and availability of physical assets essential to the operation of the enterprise as a whole. For over a decade, Engineering Industries eXcellence's team of Engineering Industries eXcellence experts has been partnering with manufacturing companies of all shapes and sizes and across all process and discrete sectors to help them identify and implement the most cost-effective Asset Performance Management strategies, technologies and solutions for their organization.
Strategies for Asset Performance Excellence
Different asset management strategies work for different enterprises: Reactive Asset Maintenance, Preventive (or Preventative) Asset Maintenance, Condition-Based Asset Maintenance, Predictive Asset Maintenance, Prescriptive Asset Maintenance and Reliability-Centered Asset Maintenance.
Level 1: Condition-Based Asset Maintenance
Sensors Monitor Asset Performance in Real Time / Maintenance is Performed When Needed
Condition-Based Asset Maintenance is a strategy that monitors the real-time functional condition of an asset to decide what maintenance needs to be done. Condition-Based Asset Maintenance dictates that maintenance should only be performed when certain indicators show signs of decreasing performance or upcoming failure. Checking a machine for these indicators may include non-invasive measurements, visual inspection, performance data and scheduled tests. Most often, conditional data is gathered at certain intervals or continuously using sensor devices in order to measure vital equipment parameters (e.g. temperature, pressure, vibration, noise).
Successful asset management solutions monitor the performance of your assets and compare that data against specifications, constraints and rules for asset usage, health and reliability. The goal of Condition-Based Asset Maintenance is to spot upcoming equipment failure so maintenance can be scheduled when it is needed, and not before, optimizing the amount of time spent on maintenance tasks. Asset conditions trigger notifications and alarms based on configurable workflows to alert maintenance teams in the moment of need, but within a long enough time period before failure, so that maintenance can be executed before the asset fails or performance falls below the optimal level.
Level 2: Predictive Asset Maintenance
Real-Time & Historical Data Predicts Failures / Maintenance is Planned in Advance
Predictive Asset Maintenance is one of the most advanced types of proactive maintenance currently available, and one of the most effective in driving a high return on assets. With time-based (preventive or preventative) maintenance, industrial organizations run the risk of performing too much maintenance or not enough. And with reactive maintenance, maintenance is performed when needed, but at the cost of unscheduled downtime. Predictive Asset Maintenance solves these issues.
Successful asset management solutions enable your different assets and systems to connect, work together, share, analyze and take action on data in order to perform analytics and enable Predictive Asset Maintenance. Predictive Asset Maintenance relies on precise formulas, in addition to condition-based measurements from sensors, to predict when asset failures will occur. Asset maintenance work is planned and performed based on the analysis of these parameters. Predictive analytics enable manufacturers to correlate factors such as historical and real-time asset performance data, maintenance records, inspection reports and environmental data in order to determine when asset degradation or failure might occur. As a result, they can then define an optimal maintenance schedule based on these analytics to minimize maintenance costs and downtime while maximizing machine utilization and throughput at the same time.
Level 3: Prescriptive Asset Maintenance
Machine Learning Predicts Failure, Identifies Reason for Failure & Appropriate Action to Take
Some asset management solutions can also enable Prescriptive Asset Maintenance, which aims to prevent the conditions that lead to machine faults and failures in the first place. Leveraging applications such as Machine Learning, Artificial Intelligence, pattern recognition and diagnostics, Prescriptive Asset Maintenance involves not only detecting degradation in assets well ahead of failure, but also identifying the reason the failure will occur and prescribing a solution to mitigate that problem.
Prescriptive Asset Maintenance is driven by models and a broad knowledge base within the system that can identify an issue, evaluate why it happened and identify or prescribe the best method for repairing it. The technique uses multiple equipment and process data variables for analysis and is best suited for the maintenance of complex assets requiring advanced skills for problem diagnosis, meaning issues that even the most experienced technician would not be able to determine by inspecting the machine or performance data alone.
Level 4: Reliability-Centered Asset Maintenance
Every Asset is Evaluated Individually to Identify Optimal Maintenance Strategy
Reliability-Centered Asset Maintenance is a corporate-level asset management strategy designed to optimize the maintenance program of an entire enterprise. The result of this approach is the implementation of a specific maintenance strategy for each of the assets within a plant, facility or company. Reliability-Centered Asset Maintenance was originally a product of airline maintenance schedules, which are among the most intensive of any industry. Airlines must undergo extensive servicing for safety, but these services must be balanced with the need for the airline to generate revenue and continue operating. Balancing these two elements is difficult as machinery is becoming increasingly complex and has multiple possible failure modes. While Reliability-Centered Asset Maintenance requires more time upfront, it helps organizations establish a maintenance plan that is both cost-efficient and equipment-effective in the long run.
The first step in Reliability-Centered Asset Maintenance is to evaluate each asset’s purpose, failure modes as well as the quantifiable impact its failure would have on the business. The process begins with these seven questions:
- What is the asset's purpose (main action) and performance standards?
- What are ways in which the asset can fail to perform its main action?
- What events are the cause of each failure?
- What happens when each failure occurs?
- How does each failure impact the system?
- What task can be performed proactively to prevent, or lessen the impact of, failure?
- What actions must be taken if a preventive task cannot be found?
Answering these questions will give the business an idea of which maintenance strategy to implement for a particular asset. In an organization that prescribes to Reliability-Centered Asset Management, one or more maintenance types may be implemented across that organization's assets.
Digital Solutions for Asset Management
Our offering covers all the solutions and services manufacturers need to manage, monitor, maintain and maximize the value of their most critical assets and infrastructure, including Computerized Maintenance Management Systems (CMMS), Enterprise Asset Management (EAM) systems and Asset Performance Management (APM) systems.
Why Asset Performance Management?
In order to increase their return on assets, leading organizations today are implementing digital solutions for Asset Performance Management. This is especially true of companies competing in industries where asset performance has a direct impact on business outputs, such as in the Energy, Utilities, Manufacturing and Transportation sectors. Asset Performance Management solutions enhance Enterprise Asset Management processes by delivering information and insights related to asset condition and performance at the point of action to minimize unplanned repair work, reduce equipment failure, increase asset availability and extend asset life without incurring unnecessary costs.
Asset Performance Management solutions track and monitor asset performance. They connect disparate sources of real-time and historical operational data in order to analyze and identify opportunities to improve asset performance, reduce maintenance costs and facilitate smarter decision-making in core business operations. They offer powerful analytics leveraging the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning, Advanced Simulation and the Digital Twin, among other enabling technologies.
Many Asset Performance Management platforms today encompass the capabilities of data capture, data integration, data visualization and advanced analytics tied together for the explicit purpose of improving the reliability and availability of physical assets. They connect your production floor to your balance sheet using data related to the health and output of your assets. They prevent asset failure and enable predictive and proactive maintenance initiatives. They help your operations and reliability leadership understand how and when assets fail, enabling them to make changes and improve performance. They also enable you to evaluate the financial risks and rewards of different asset investment and management strategies. They can even leverage asset data from existing enterprise software systems, including Automation & Control, Enterprise Resource Planning (ERP), Manufacturing Execution Systems (MES) and Product Lifecycle Management (PLM) systems.
Engineering's Expertise
The strategy which an organization employs to manage the performance and maintenance of critical infrastructure and assets plays a major role in the productivity and profitability of the business as a whole. In manufacturing, studies show that unplanned machine downtime can cost an enterprise 10 times more than planned maintenance due to the disruption to business and lost production. Our Engineering Industries eXcellence division designs and delivers proven technology solutions for Asset Performance Management, Intelligent Asset Monitoring and Asset Maintenance Management to industrial customers across all manufacturing industries worldwide. By integrating process visibility, data intelligence, pattern recognition and predictive analytics into their asset management portfolios, we enable asset-centric organizations to ensure the performance of their assets while reducing operational costs and business risks at the same time.
