Table of Contents
- Executive Overview
- Improving Maintenance and Operations
- Industrial IoT Case Stories
As new technology approaches, both Industrial IoT (IIoT) and Industrie 4.0 provide opportunities for owner-operators to improve overall business performance, including asset performance management (APM). This includes operational and business process improvements through removing waste and/or faster workflow. For original equipment manufacturers (OEMs), IIoT offers new sources of revenue by extending the company’s business model into aftermarket services
ARC Advisory Group has been performing research into APM for many years now and recently updated our APM model to reflect the new technology solutions now available to industrial organizations and their OEMs. An “APM 2.0” strategy involves information sharing and application integration among operations and maintenance to provide a comprehensive view of production and asset performance. This incorporates IIoT, analytics, and other predictive and prescriptive technologies to bring performance to a higher level.
At a recent ARC Industry Forum, we saw three case study presentations exemplifying the benefits of this strategy:
- CSX Transportation for critical, mobile asset
- CERN for the largest and one of the most complex machines on the earth (with millions of components)
- BOR for a foundation of excellent asset document management
The key findings for owner-operators encompass getting started with IIoT for a pilot project:
- Start predictive maintenance pilot projects using an IIoT approach
- For future equipment purchases, include IIoT and predictive maintenance (PdM) as critical selection criteria
- Choose an IIoT platform for the time-stamped data, analytics, and alerts that scales to allow you to build on success with later projects
- In parallel, establish governance for document management and data integrity to support a robust IIoT and business process improvement program
Improving Maintenance and Operations
Per surveys conducted by ARC Advisory Group, the primary driver of IIoT and enterprise asset management (EAM), a key enabler for improving APM, involves reduced machine downtime.
EAM helps assure that the needed skills, parts, and documentation converge to support high-quality maintenance of assets. This reduces mean time to repair (MTTR) when a fault occurs. Also, EAM systems are used to schedule preventive maintenance to help prevent many failures.
IIoT takes this a step further through its support for PdM. With IIoT, equipment-related data is combined with analytics to help assess an asset’s health for early detection of a fault before failure and unplanned downtime occur. Detecting and repairing a fault before it cascades into extensive destruction of other parts and equipment significantly reduces the costs for repair and avoids costly unplanned downtime.
Improving Business Performance
IIoT and Industrie 4.0 offer examples of new technologies that provide an opportunity to improve business performance for both owner-operators and OEMs:
- Plant owner-operators: Operational and business process improvements through removing waste and/or better work flow
- Original Equipment Manufacturers: New sources of revenue by extending the company’s business model into aftermarket services
Operational Improvements for Owner-Operators
The first benefit, operational improvements, applies to plant owner-operators in two distinct areas: predictive maintenance and optimizing operations.
Predictive Maintenance by the Owner-Operator
The leading use of IIoT involves predictive maintenance for particularly critical, expensive, and/or problematic assets. These situations frequently get close management attention because of the often high dollar impact on the organization’s ability to make product and produce revenue. With the clear financial benefits, even complex custom projects using IIoT, analytics, networking, and equipment modifications typically get approved.
IIoT provides equipment data (like current draw) for analysis with existing sources of process data (like flow rate). Since historians typically connect to process control systems, they contain process data. IIoT connects to the equipment, providing equipment data. Analytics using data from both operations and equipment provides new opportunities for coordinating resources and information to improve asset performance management (APM).
Revenue Enhancement for OEMs
IIoT provides OEMs with two distinct ways to enhance its products and grow revenue. One involves improving the equipment design; the other adds aftermarket services.
Closed-loop Product Lifecycle Management (PLM)
Most equipment manufacturers ship products and never obtain feedback on performance - until something goes wrong and the customer complains. Other than testing some prototypes, product development is often performed "open loop," without direct customer feedback. However, with IIoT, product designers can “close the loop” using IIoT-derived data from a variety of field operating environments. Analyzing these data for product development provides opportunities to optimize designs, gain a competitive advantage, and grow market share for increased revenue for existing product lines.
Predictive Maintenance by OEMs
When a critical piece of equipment fails, production can be interrupted, affecting shipments and revenue. To achieve quick repair, the owner-operator has its own on-site maintenance staff. Most OEM’s services strategy supports these resident maintenance technicians. With IIoT- enabled remote monitoring and PdM, OEMs have an opportunity to significantly expand services with new sources of revenue.
No one knows the equipment better than the OEM that designed it. The OEM can develop analytics that use IIoT data to assess condition and provide value-added PdM services that inform users of a pending issue before they experience the problem. The OEM sells PdM services and technical support to achieve near-zero unplanned downtime for its equipment installed in customer plants. The support can be offered as an aftermarket subscription in various levels from a simple email alert service with a help desk, to having the OEM’s field service technicians make repairs.
Preventing Lost Alerts and Improving Data Quality
IIoT-enabled asset health monitoring solutions can generate alerts when an issue arises. But what happens next? Responses from ARC surveys indicated that “ad hoc communications” is the most common method used to transfer an alert to maintenance. These ad hoc communications can include email, phone calls, or even a chance meeting in the hallway. As a result, alerts are often lost and the equipment fails just as predicted.
By automating these types of business processes, owner-operators can capture alerts to prevent unplanned downtime. IIoT-derived equipment data goes into the historian and analytics (either custom algorithms or machine learning) to assess equipment health. In the following diagram, the PdM system has access to both process and equipment data. Alerts generated by the PdM system are automatically transferred to the EAM system, which automatically generates a maintenance work order for review, approval, and scheduling by the maintenance planner.
Mobile devices allow technicians to process the work order while they are doing the work. Mobility solutions can also help improve data quality and timeliness in the EAM system.
Asset Performance Management
APM involves improved integration between production management (making the product) and asset management (ensuring the capability to produce). This integration can increase visibility, collaboration, and communication to increase productivity, reduce risk, and improve return on assets (ROA). Goals and objectives become more clearly communicated and shared. The ramifications extend into business processes, technology, and organizational structure.
An APM 2.0 strategy includes information sharing and application integration among enterprise asset management (EAM), manufacturing execution systems/manufacturing operations management (MES/MOM), plant asset management (PAM), and other solutions to provide a comprehensive view of production and asset performance.
APM 2.0 incorporates IIoT, analytics, and other predictive and prescriptive technologies to bring performance to a higher level. It provides a means to systematically improve key metrics like uptime, mean time to repair (MTTR), asset longevity, cost, quality/yield and safety for maintenance; and on-time shipment, quality, and inventory for operations. This optimization spans functional silos, particularly between silos where significant inefficiency, waste and sometimes dysfunction often reside. Rather than accepting waste among APM functions, ARC recommends that industrial organizations develop a disciplined approach for improvements.
For more on APM2.0, ARC clients should refer to our September 2015 Strategy Report “APM 2.0 with Industrial IoT.”
Readers can also see a video recording of the author’s recent Forum presentation on ARC’s YouTube channel. The following sections of this report summarize the end users case from that Forum session.
Industrial IoT Case Stories
As illustrated by the following case studies, emerging technologies – especially IIoT and analytics – have opened an opportunity for near-zero unplanned downtime while improving asset longevity and costs.
CSX Transportation Improves Uptime with Lower Costs
Bill Larson, Director, Process Improvement, CSX Transportation, presented “On Track Work Equipment EAM Wireless Sensor – PM Integration.” As a major railroad, CSX provides rail-based freight transportation and services in North America, including intermodal containers. CSX Transportation encompasses about 21,000 route miles of track in 23 states, the District of Columbia, and the Canadian provinces of Ontario and Quebec. Some two-thirds of Americans live within CSX’s service areas.
Rethinking Asset Management
The combination of aging infrastructure and industry dynamics for safety, regulations, growth, and competition exerts pressure for railroad operators to rethink how to manage their geographically dispersed assets. New technologies combined with innovation provide opportunities to lower maintenance costs while improving KPIs like uptime and mean time between failures (MTBF). At CSX, this realization drove a transformation to intelligent, interconnected, instrumented, and – ultimately -- optimized assets.
Mr. Larson’s presentation focused on CSX’s “Work Equipment” class of assets for upgrading its railway track. In total, Work Equipment includes 3,500 individual machines. This includes complex tamper machines to restore the track surface following replacement of ties and/or track.
The project’s objective involved improving equipment reliability (uptime and MTBF) and utilization (extend time between rebuild cycles) with lower maintenance costs. An initial study proved that the OEM’s current recommendation to change the oil and filter in the tamper every month was too conservative. Based on an initial study, the oil and filter replacement time was extended from 30 days to 45 days, saving $1.3 million in filters and labor alone. Further analysis showed that, with predictive maintenance, the change cycle could be extended to 60 days and save an additional $1 million annually in filters and labor.
PdM required communications for gathering data on runtime and other operating statistics. At about this time, new regulations for commercial driver electronic logbooks drove an investment in communications. An evaluation determined that this new infrastructure could be leveraged for the communications needed to support PdM.
The CSX PdM application performs analytics that identify a problem before it can lead to a failure. Integration with the IBM Maximo EAM system automatically generates maintenance work orders. The maintenance planner approves and schedules these work orders in Maximo, and then sends them to the technicians in the field. Completion is fed back into Maximo.
With this business process automation, data quality improved and management learned to trust the data. Also, PdM mitigated risk. Approval was given to go with a 60-day cycle for changing filters in the tamper machine. Extending the preventive maintenance (PM) cycle without impacting reliability saved a total of $2.3 million annually, plus productivity improvements.
A video recording of Mr. Larson’s Forum presentation is available here.
CERN Employs IIoT to Maximize Machine Uptime
David Widegren, Head of Asset & Maintenance Management, CERN, Geneva, Switzerland presented “CERN: Maximizing Uptime for the World’s Largest and Most Complex Machine.” CERN (European Organization for Nuclear Research) is the world’s largest research center for particle physics with 21 European member states and another 86 collaborating countries (including the US).
The Large Hadron Collider (LHC) at CERN contains about 100 million high-tech components for a 17-mile circular tunnel that is 330 feet below ground and cost $8+ billion. In it, sub-atomic particles are accelerated to nearly the speed of light to recreate a small version of the “big bang” at the beginning of our known universe.
Managing Millions of Assets
CERN uses Infor EAM to manage 1.8 million critical assets for both the particle accelerator equipment and the site infrastructure. This system has 1,100 users and processes 150,000 work orders per year. Assets at CERN often have a lifecycle exceeding 50 years. The long lifecycles, combined with the much faster turnover of personnel, make documenting both assets and interventions critical to success. This includes an inventory of the assets with detailed technical characteristics. CERN integrated the EAM system with over 20 other systems, including document management, control room, radioactive tracing, manufacturing, ERP, SCADA, GIS, reporting, and IoT-networked equipment.
At CERN, the wide variety of casual users (from research PhDs to technician contractors) makes ease-of-use critical, since most users receive only limited training. Since different users have specific needs, the software has configurable profiles to fit the various types of users. The simplified interface is available on mobile devices, enabling broad user adoption with a high compliance rate.
CERN outsources over half of the maintenance. A common tool allows for shared methods and best practices, which in-turn brings operational efficiency and significant financial savings. The contractors fully comply with using Infor EAM, since managing work orders is a prerequisite for payment for their services.
PdM Benefits for Elevators
Using IIoT to streamline maintenance, CERN integrates the SCADA systems connected to the accelerator equipment. The LHC elevators are critical assets since they provide access to the accelerator 300 feet below ground. According to Mr. Widegren, integrating Infor EAM and Siemens WinCC optimizes the scheduled preventive maintenance to help achieve 50 percent less maintenance with a 5 percent increase in availability. CERN also uses IIoT for asset health monitoring and PdM that allows an asset to “raise a flag” to the EAM system when it has a problem.
When applying IIoT to maintenance, Mr. Widegren recommended filtering data for what is important, and go from “Big Data” to “Right Data” (see August 24, 2014 ARC Insight, “Small Data for Enhanced Asset Performance”). CERN stores half a terabyte of data per day for the accelerator performance (much less than the 100 terabyte of physics data stored daily). EAM is used to identify the critical assets and allow better filtering and interpretation of the “Big Data noise.” “Combining enterprise asset management with Industrial IoT enables us to maximize uptime and optimize accelerator performance, which in turn is the way forward to new discoveries that can change our understanding of the universe,” commented Mr. Widegren.
A video recording of Mr. Widegren’s Forum presentation is available here.
US Bureau of Reclamation Document Management
Gary McDanel, Manager, Information Management Group, US Bureau of Reclamation (BOR), presented “Maintain Asset Data Integrity and Reap the Benefits of the ‘Internet of Things.’” The US Bureau of Reclamation manages water in the western US under the 1902 Reclamation Act because, according to Mr. McDanel, “Water makes dirt valuable.” In this role, it is the largest water wholesaler and second largest electric power producer in the US. In the 17 states, it manages 600 dams, reservoirs and canals; and 53 hydro power plants that bring water to 31 million people.
BOR has 10 million drawings and 9,000 employees in the 17 western states. The asset replacement cycle typically takes 50 years. An extreme example is Hoover Dam which has a life expectancy of 300 to 500 years based on how long it is anticipated for the lake to fill with sediment. The dam itself is designed for thousands of years. The Bureau manages documents for the life of these assets.
BOR had documents scattered in multiple locations with no version control and independent edits. The first attempt at a document management system failed due to changing technologies and suppliers that disappeared. The second approach, using BlueCielo ECM, was successful.
A broad number of internal groups and external organizations use the BOR’s documents. A key objective for the new system included version control (to help ensure one current version) and governance (to manage read and write privileges). Also, the system needs to comply with Department of Interior’s policy to consolidate and centralize document management. BOR selected BlueCielo ECM for the project based on its ability to meet these and other needs.
Following implementation, every night, servers in 16 locations now sync-up with the central server. With just 18 months since implementation, the system now houses two million documents.
Getting user buy-in required onsite training in each of the satellite offices by a core team of experts with deep knowledge of the application and its deployment. These experts could respond to local issues while still maintaining consistency where needed across the locations. Though costly, this approach was effective. A previous attempt, using a “train the trainer” approach failed due to lack of knowledge and consistency.
Mr. McDanel shared the following lessons learned:
- Include the end users in building requirements and system roll-out.
- Acceptance of a project is directly related to the quality of the training.
- Address issues raised by users quickly. In a networked world, bad news travels fast, and one person can create a lot of pushback. Also, enable the leading satisfied users to become local supporters and advocates.
Future plans include:
- Integrate the BlueCielo ECM solution with the IBM Maximo EAM system to provide real-time access to current drawings for maintenance planning, execution, and safety.
- With 80 percent of drawings remaining on paper, continue migration to digital.
- Using IIoT, have a predictive maintenance program for the equipment with automatic generation of work orders in the EAM system.
Good documentation management provides a foundation to help assure the high data quality needed to support IIoT initiatives.
A video recording of Mr. McDanel’s Forum presentation is available here.
In these case stories and others reviewed by ARC, the “low hanging fruit” for IIoT involves asset health monitoring and preventing unplanned downtime.
To be able to realize similar benefits from an IIoT initiative, ARC recommends that owner-operators start a pilot project using an IIoT approach for a pilot project for predictive maintenance. The steps follow:
- Identify equipment that causes unplanned downtime and rank the associated impact by the cost of the associated production disruption. In most plants, the culprits are well known to production supervisors. If management requires a more thorough analysis and ranking to approve the project, consider employing the reliability centered maintenance (RCM) methodology.
- For a pilot project, evaluate the existing sensors and communications for the more egregious equipment to determine a likely candidate for the pilot. Retrofitting equipment adds cost, time, and project risk. Avoid these risks for the initial project.
- Choose an IIoT platform for the time-stamped data, analytics, and alerts that can scale to enable you to build on the initial success with additional projects later. ARC can help point owner-operators toward the suppliers in this space with the appropriate capabilities from which to create a short list for further evaluation.
- For future purchases of equipment, include IIoT and PdM as critical selection criteria. In particular, this applies to the more complex devices for which on-site, general-purpose technicians may not have the specific training, expertise, tools and experience required to trouble shoot, isolate problems, and effect appropriate repairs.
Also, “reserve the date” for the next ARC Industry Forum, Accelerating Digital Transformation in Energy & Cities, February 16-17, 2021 – Online. IIoT and digital transformation will continue to be key topic areas.
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