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INTERACTIVE GUIDE

Elevate Your Performance with Maintenance 4.0

Increasing asset lifecycle and human productivity with digital technology.

Nobody Disputes the Notion That Every Organization Must Move Toward Prescriptive Maintenance

Too few know where and how to begin, let alone get there. Most executives and maintenance professionals understand the transition involves deploying the latest digital technologies, a trend dubbed Maintenance 4.0, which increases the uncertainty further.

The goal of Maintenance 4.0 is to increase asset lifecycle and human productivity through the application of Industry 4.0 technologies—data and analytics, machine learning, automated processes, robotics, and drones—to reliability and maintenance activities.

This interactive guide offers a closer look at how organizations can create a strategy leveraging the latest digital technology to propel asset maintenance from a cost center to a strategic imperative and achieve the goals of Maintenance 4.0.

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$ 0 Billion

average annual cost of unscheduled downtime in the process industries = almost 5% of production.

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$ 0 K / hr.

per hour cost of unplanned downtime across all business

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INDUSTRY TRENDS

Reducing Unplanned Downtime and Helping Future-proof Automation System Assets

Unplanned downtime is the number one issue for automation systems today. A significant percentage of today’s global installed base of automation systems are at least 20 years old and becoming increasingly difficult and costly to maintain properly.

The Opportunities

The impact of digitized asset management or the lack of it will permeate every aspect of a business.

A best-in-class asset management system:

Includes Safety Specifications
Includes Safety Specifications
Safety Specifications
Keep assets operating safely within specifications, producing higher quality products, and delivering better service.
Extends<br />
Lifecycles
Extends
Lifecycles
Extended Lifecycles
Improve return on assets (ROA) by extending assets’ lifecycles.
Increases<br />
Efficiency
Increases
Efficiency
Increased Efficiency
Optimize energy use and ensuring operators spend time on value-added activities.
Ensures Regulatory Compliance
Ensures Regulatory Compliance
Regulatory Compliance
Achieve better regulatory compliance and Service Level Agreement (SLA) adherence.

Operational

  • Fewer breakdowns = reduced downtime + fewer scheduled repairs + lower maintenance costs + happier customers
  • Lower maintenance cost + higher workforce utilization =  higher productivity + increased production growth + higher OEE

Financial

  • Lower maintenance costs + reduced inventory/MRO cost + reduced CapEx = higher gross margins + better operating margins

3 Critical Guidelines

Develop the
Business Case

Determine your investment strategically based on expected ROI. Don’t make an investment that can’t be justified to shareholders.

Moving to Maintenance 4.0

Adopt incrementally—Build on existing processes, practices, and even technology. Avoid products that are still evolving.

Data is the Driver

Often referred to as the oxygen of Maintenance 4.0, data from embedded sensors must be managed with strong governance practices to ensure its value is captured.

Leverage the Maintenance Maturity Model

The Five Levels of Maintenance Maturity

Reactive – allow assets to run until failure before repairing

Mindset: Since maintenance is a cost center, any effort to proactively maintain equipment is a waste of resources.

Explanation: Manufacturers avoid spending money on or taking resources out-of-service until necessary.

Example: When an automatic conveyor belt breaks down, the line shuts down, idling operators and delaying deliveries to customers until the cause of the breakdown is determined, replacement parts are ordered and arrive, and maintenance fixes the conveyor.

Data and technology: Reactive maintenance requires no data or technology. To move to the next level, companies must gather basic maintenance data and set up rudimentary maintenance schedules, at minimum, the equipment manual and a calendar. Some companies may also collect actual performance data in manual or spreadsheet-based logs. Still others will invest in computerized maintenance management systems (CMMS), which maintains a computer database of information about an organization's maintenance operations. The most advanced companies will deploy EAM systems to help track and manage maintenance routines and MRO inventory.

Preventative – complete routine inspections and full or partial service on a fixed schedule

Mindset: The value of avoiding the unplanned downtime that results from reactive maintenance is higher than the cost of proactive maintenance.

Explanation: Organizations spend money and take a resource offline to complete minor maintenance to avoid an unplanned shutdown, reduce risk, and increase safety as well as extend mean-time-between-failures and equipment lifespan.

Example: The maintenance staff inspects the conveyor belt and completes service at regular intervals, which keeps malfunctions at a minimum but leaves them exposed to malfunctions. When breakdowns occur, the organization has replacement parts on hand to speed repair.

Data and technology: As organizations realize the benefits of proactively maintaining equipment, they begin to seek more maintenance data. Often, they identify a specific problem area that is the cause of most malfunctions on a vital asset, so they push to automate monitoring it using sensors that send alerts to an EAM system.

Condition-based monitoring – closely monitor one or a few vital parameters of a critical piece of equipment

Mindset: Identifying and closely monitoring metrics or key performance indicators on a machine that is central to productivity will increase the effectiveness of preventive maintenance.

Explanation: Manufacturers automate the collection of data that will predict when an asset is likely to fail and send an alert. With the advance notice, maintenance intervenes to fix an out-of-spec condition before it causes a failure.

Example: Since data collected in earlier preventive efforts show that conveyor belt malfunctions tend to result from, say, vibration and overheating in a conveyor belt motor, the maintenance staff uses sensors to monitor those parameters and arrange for alerts to be sent via the EAM to the right personnel who quickly address the problem, limiting unplanned downtime.

Data and technology: Sensors and an EAM system automate monitoring and failure alerts. Moving to the next level requires the automated collection and analysis of more data from more equipment, which requires the use of advanced data management technologies, prompting manufacturers to leverage cloud-based systems in addition to on-premise computing.

Predictive – extending automated monitoring to all aspects of an increasing number of assets

Mindset: Realizing the tangible and intangible benefits of avoiding unplanned downtime, manufacturers view enterprise asset management as a strategic imperative.

Explanation: As data accumulates and is compiled and analyzed, the EAM system predicts with increased precision when an asset is likely to malfunction. With these insights, manufacturers complete maintenance at the right time, neither too late, after a malfunction, nor too early, wasting resources. Armed with advanced automated notice of potential failures throughout the facility, manufacturers further reduce the negative consequences of unplanned downtime throughout operations.

Example: With the entire conveyor belt system being continually and automatically monitored, along with other assets throughout the factory, maintenance staff is alerted and can fix problems before they impact production while getting maximum lifespan from machine parts.

Data and technology: With more data available, advanced analytics, including artificial intelligence and machine learning are deployed, allowing the system to continue to perfect predictions. To manage the massive amounts of data, manufacturers must optimize data management and computing systems, often adding edge computing—where data collection storage and analysis are completed near a device, reducing latency and bandwidth usage.

Prescriptive – automating not only data that predicts failure but also the accumulated knowledge of how to rectify the problem that will cause the failure

Mindset: Understanding the strategic implications of an EAM strategy that leverages the latest smart manufacturing technologies, asset management becomes part of a company’s overall business system.

Benefit: With enterprise asset management integrated with other business functions, the organization can quickly adapt to a variety of business situations, whether disruptions in the supply chain or unexpected increase in demand, in addition to keeping equipment running safely at peak.

Example: The sensors monitoring an asset detect an anomaly in one part of the conveyor system, analyze the dataset associated with it, then alerts maintenance personnel while simultaneously identifying (and ordering, if needed) the spare parts and tooling they need. The maintenance staff interacts with the system as it offers step-by-step instructions on how to make the repair.

Data and technology: A prescriptive system integrates multiple systems, including EAM, inventory, and reliability-centered maintenance systems. It automatically coordinates all elements in real time and uses algorithms that learn and get smarter over time. When implemented, the manufacturer has achieved the Industry 4.0 goal of leveraging cyber-physical systems.

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Reactive – allow assets to run until failure before repairing

Mindset: Since maintenance is a cost center, any effort to proactively maintain equipment is a waste of resources.
Explanation – Manufacturers avoid spending money on or taking resources out-of-service until necessary.
Example: When an automatic conveyor belt breaks down, the line shuts down, idling operators and delaying deliveries to customers until the cause of the breakdown is determined, replacement parts are ordered and arrive, and maintenance fixes the conveyor.
Data and technology: Reactive maintenance requires no data or technology. To move to the next level, companies must gather basic maintenance data and set up rudimentary maintenance schedules, at minimum, the equipment manual and a calendar. Some companies may also collect actual performance data in manual or spreadsheet-based logs. Still others will invest in computerized maintenance management systems (CMMS), which maintains a computer database of information about an organization's maintenance operations. The most advanced companies will deploy EAM systems to help track and manage maintenance routines and MRO inventory.

Preventative – complete routine inspections and full or partial service on a fixed schedule

Mindset: The value of avoiding the unplanned downtime that results from reactive maintenance is higher than the cost of proactive maintenance.
Explanation – Organizations spend money and take a resource offline to complete minor maintenance to avoid an unplanned shutdown, reduce risk, and increase safety as well as extend mean-time-between-failures and equipment lifespan.
Example: The maintenance staff inspects the conveyor belt and completes service at regular intervals, which keeps malfunctions at a minimum but leaves them exposed to malfunctions. When breakdowns occur, the organization has replacement parts on hand to speed repair.
Data and technology: As organizations realize the benefits of proactively maintaining equipment, they begin to seek more maintenance data. Often, they identify a specific problem area that is the cause of most malfunctions on a vital asset, so they push to automate monitoring it using sensors that send alerts to an EAM system.

Condition-based monitoring – closely monitor one or a few vital parameters of a critical piece of equipment

Mindset: Identifying and closely monitoring metrics or key performance indicators on a machine that is central to productivity will increase the effectiveness of preventive maintenance.
Explanation: Manufacturers automate the collection of data that will predict when an asset is likely to fail and send an alert. With the advance notice, maintenance intervenes to fix an out-of-spec condition before it causes a failure.
Example: Since data collected in earlier preventive efforts show that conveyor belt malfunctions tend to result from, say, vibration and overheating in a conveyor belt motor, the maintenance staff uses sensors to monitor those parameters and arrange for alerts to be sent via the EAM to the right personnel who quickly address the problem, limiting unplanned downtime.
Data and technology: Sensors and an EAM system automate monitoring and failure alerts. Moving to the next level requires the automated collection and analysis of more data from more equipment, which requires the use of advanced data management technologies, prompting manufacturers to leverage cloud-based systems in addition to on-premise computing.

Predictive – extending automated monitoring to all aspects of increasingly more assets

Mindset: Realizing the tangible and intangible benefits of avoiding unplanned downtime, manufacturers view enterprise asset management as a strategic imperative.
Explanation: As data accumulates and is compiled and analyzed, the EAM system predicts with increased precision when an asset is likely to malfunction. With these insights, manufacturers complete maintenance at the right time, neither too late, after a malfunction, nor too early, wasting resources. Armed with advanced automated notice of potential failures throughout the facility, manufacturers further reduce the negative consequences of unplanned downtime throughout operations.
Example: With the entire conveyor belt system being continually and automatically monitored, along with other assets throughout the factory, maintenance staff is alerted and can fix problems before they impact production while getting maximum lifespan from machine parts.
Data and technology: With more data available, advanced analytics, including artificial intelligence and machine learning are deployed, allowing the system to continue to perfect predictions. To manage the massive amounts of data, manufacturers must optimize data management and computing systems, often adding edge computing—where data collection storage and analysis are completed near a device, reducing latency and bandwidth usage.

Prescriptive – automating not only data that predicts failure but also the accumulated knowledge of how to rectify the problem that will cause the failure

Mindset: Understanding the strategic implications of an EAM strategy that leverages the latest smart manufacturing technologies, asset management becomes part of a company’s overall business system.
Benefit: With enterprise asset management integrated with other business functions, the organization can quickly adapt to a variety of business situations, whether disruptions in the supply chain or unexpected increase in demand, in addition to keeping equipment running safely at peak Example: The sensors monitoring an asset detect an anomaly in one part of the conveyor system, analyze the dataset associated with it, then alerts maintenance personnel while simultaneously identifying (and ordering, if needed) the spare parts and tooling they need. The maintenance staff interacts with the system as it offers step-by-step instructions on how to make the repair.
Data and technology: A prescriptive system integrates multiple systems, including EAM, inventory, and reliability-centered maintenance systems. It automatically coordinates all elements in real time and uses algorithms that learn and get smarter over time. When implemented, the manufacturer has achieved the Industry 4.0 goal of leveraging cyber-physical systems.

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Adopting Maintenance 4.0 technology in EAM

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Digitized Asset Records

The first step, for many organizations, will be to move from a paper-based record management system to a digitized system.

Cloud & Connectivity

Many organizations still have several separate systems tracking various aspects of asset management, such as reliability, labor, procurement, and others. By definition, Maintenance 4.0 demands connectivity—between and among machines and people. Cloud-based systems collect data in a single, easily accessible repository, which enables engineers, executives, and technicians to gain actionable insights.

Reliability

Eliminating failure modes and minimizing the frequency of unplanned downtime can deliver substantial financial benefits.

Labor

Adding engineers’ qualifications, certifications, location, and availability ensures that the right level and caliber of labor is scheduled, which drives quicker resolution, greater accuracy, and higher workforce utilization.

Procurement

Linking procurement and inventory systems assures that the correct part or supply is available when needed at the right time, without overstocking.

Connecting systems to engineers’ workstations or handheld or mobile devices makes it possible for field techs to access work orders, instructions, warranties, diagrams, manufacturers’ specifications, and more while on site. Such capabilities improve the timeliness and accuracy of inspections, repairs, and reporting, saving technicians an average of 45 minutes per day.

As computing resource demand increases, integrating a third level of data capture and analysis helps in a variety of ways. Computing at the edge locates resources near devices such as vision systems, so the data collected from them doesn’t have to travel to the central resource. This reduces bandwidth demands on the network as well as latency issues.

Advanced sensors placed on every critical asset, along with edge devices, gather data and feed it to the cloud system, which provides more advanced analytical and diagnostic capabilities.

With data in one location and maintenance systems integrated, dedicated alerts and updates can be set to notify responsible parties when an asset requires attention.

With integrated automated systems collecting and storing data in the cloud, analytics and business intelligence systems can extract and contextualize information and deliver higher-level insights.

Once a model is determined, and algorithms are deployed, machine learning technology will ensure the system finds hidden patterns and continuously improves according to actual conditions.

With mixed reality, users can interact in real time with virtual objects that are within the real world—and the objects will respond and react to users’ actions. These capabilities can facilitate training, assist repair and replacement operators by providing instructions, and allow remote adjustments of equipment.

Connecting robots and drones to the system allows for their deployment to complete maintenance tasks that are dirty, dull, or dangerous, which keeps employees safe and focused on more value-added maintenance duties.

Geographic Information Systems (GIS) – Deploying Geographic Information Systems and Global Positioning Systems (GPS) enables more precise tracking and management of assets that are on the move, such as vehicle fleets. With the ability to pinpoint the exact routing and location of each asset, via GIS coordinates, personnel can optimize inspection and maintenance.

Proven Best Practices Case Studies

Asset-intensive industries, such as transportation, energy, cities, and process and discrete manufacturing, simply cannot deliver products and services if their assets fail.

That’s why companies operating in these industries are on the leading edge of leveraging Maintenance 4.0 capabilities. Take a look.

invenergy2

Invenergy digitizes field work with Infor CloudSuite EAM Mobile

Watch the video to see how Invenergy’s switch to EAM Mobile has digitized their maintenance system, allowing the company to collect and track asset data more efficiently.

auckland

Auckland Transport streamlines field maintenance with Infor CloudSuite EAM Mobile

Auckland Transport plans to use CloudSuite EAM to manage the maintenance of bridges and walls across Auckland, New Zealand over the next several years.

lp-buildingsolutions

LP Building Solutions reduces downtime and cuts costs with Infor CloudSuite EAM

LP Building Solutions set out to transform its corporate culture, empowering employees to improve operations and increase revenues—not just through robust sales of its award-winning products, but by also focusing on Overall Equipment Effectiveness (OEE).

wepa-group-image

WEPA Group drives growth and operational efficiency using Infor CloudSuite EAM

The WEPA Group is a European market leader in the manufacture of hygiene paper products. To stay competitive in the capital- and energy-intensive industry, the company needed to improve its operational efficiency.

city-of-greensboro-sm

City of Greensboro creates efficiencies with Infor CloudSuite EAM

The City of Greensboro is the third-largest city in North Carolina. City staff use Infor® CloudSuite EAM to manage
900,000 assets and systems.

sapphire-sm2

Strathclyde Partnership for Transport keeps assets on track with Infor CloudSuite EAM

Funded by 12 councils across Glasgow and the West of Scotland, Strathclyde Partnership for Transport (SPT) is the largest of Scotland’s seven regional transport partnerships and is responsible for the development and delivery of the Regional Transport Strategy.

Make Your Move

By making in-depth analysis of data possible, EAM is a critical element, a central building block for achieving enterprise-wide maintenance 4.0 asset management.

But not all EAM solutions are the same. Some critical considerations include the following:

Does the EAM feature integrated advanced capabilities, or are these capabilities offered as add-on modules that will require time and resources to custom code and test? Consider the following:

  • Energy optimization
  • Reliability-centered maintenance
  • Scheduling
  • Checklist functionality
  • Secure contractor portal
  • Facilities management tools

Maintenance professionals need access to the EAM system where they are, usually where the equipment is. Can the EAM do the following?:

  • Offer true mobility that doesn’t require full connectivity to be used
  • Run on any mobile platform or device, or is it limited by the operating system provider
  • Adapt to your business processes, rather than the other way around

No business remains the same for long, nor should its maintenance strategy. Consider how flexible the EAM is; does it:

  • Operate in the cloud, on-premise, or in a hybrid environment
  • Offer choice of cloud model
    – Multi-tenant model allows you to scale up and down as needed
    – Single-tenant hosts your system in your secure environment
  • Grow with your needs and support as many concurrent users as you may need—without having to worry about it crashing.

With Maintenance 4.0, connectivity is expected. EAM systems must easily integrate with other business systems and software, such as:

  • Enterprise Resource Planning (ERP)
  • Human resources
  • Finance

Above all, maintenance personnel needs to focus on maintaining assets—not on figuring out and maintaining a complicated, buggy software program. Choose a solution that is highly configurable and doesn’t require customization.

Conclusion

By deploying Maintenance 4.0 technologies to enterprise asset maintenance management and operations, the decision-making process is driven by the AI that mines big data generated by sensors.

This data is then studied by ML to identify patterns and deliver instant, understandable, actionable information to make sure assets perform optimally. By using sensors and other technology, operators no longer waste time going to gather information nor take the time to analyze it manually. Instead, the data are available when and where the operator needs it.

As organizations leverage these technologies to automate and optimize operations, business leaders can turn their attention to how their new Maintenance 4.0 capabilities can strengthen or create new, strategic competitive advantages.

Additional Resources

  • HOW-TO-GUIDE
shipmentcontainerdock

Configuration vs customization—how to tell the difference, and which one to embrace

The more complex your requirements, the less likely it is that a piece of commercial software is going to come out of the box meeting those requirements.

  • INFOGRAPHIC
2nd-resource-thumbnail

You can’t manage what you don’t measure

Overall equipment effectiveness (OEE) is the gold standard for measuring productivity.

  • EXECUTIVE BRIEF
infor-enterprise

Understanding the Enterprise Asset Maintenance Maturity Model

Learn about the benefits, drawbacks, and strategic considerations at each stage of maintenance maturity.

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