1st Keynote Address
Value and Risk Based Asset Management by John Mitchell, Meridium, Inc.
One of the primary challenges facing any asset management program is prioritizing opportunities to match resources - a crucial bridge for there is always more of the former than the latter! Rather than beginning an optimizing process from the bottom with one or more programs such as RCM, RCA, CBM, Work Management, etc, industry leaders are beginning to identify opportunities from the top based on statistical analysis and factors such as risk, lost production and increased business value.
In this sequence, programs, practice and technology are selected to address and provide greatest results for specific improvement opportunities. This is far more effective when compared to selecting a program first and hoping value will be discovered somewhere along the implementing path. In addition to the well-known Pareto analysis, leaders are utilizing Weibull and comprehensive risk analyses to identify and prioritize improvement opportunities by potential business value. Whether these or other methods are employed; accurate, accessible data, powerful analytical methods and reliability professionals who can successfully bridge from business objectives to value directed technology and practice are a must.
The concept of asset management as a top down, master process driven by statistical analyses of variations from performance and cost objectives may be somewhat unconventional. With that stated, centering an asset management program upon the localization and prioritization of opportunities for improvement by value potential offers major opportunities for increased effectiveness during initial implementation as well as within a mature program.
This presentation will outline the processes used by several industry leaders, factors driving them in this direction and imperatives for success.
Paper 1
The Role of the Reliability Engineer in a World of Conflicting Priorities by Robert DiFrancesco, ARMS Reliability Engineers, LLC
Owner/Operators are under increasing pressure to generate as much revenue as possible out of existing assets and unfortunately depleting resources. To have any hope to accomplish this seemingly impossible task the organization must develop an Optimized Asset Management Strategy (OAMS). An OAMS provides a cost effective maintenance plan to assure the assets will meet all short and long term business requirements at the lowest possible overall business cost. The keystone to developing this plan is the use reliability tools (Root Cause Analysis, Reliability Centered Maintenance, Reliability Block Diagrams, etc.). The purveyor of these tools is the Reliability Engineer. Unfortunately with the continued trend toward doing more with less and the combining of responsibilities, few organizations have the luxury of dedicated Reliability Engineer. In addition to burden of seemingly continuous reorganization, the plant engineers, including the Reliability Engineer are asked to participate in more and more initiatives. Most of these initiatives (TPM, Kaizen, Six Sigma, 5S, Lean, PSM, ISO, etc.) are important and can be very effective at improving plant performance. They are somewhat intertwined or at least complimentary with Reliability. They are a resource draw, however, and Reliability Engineers, as leaders in the plant are often called upon to participate. Soin this world of depleting resources and conflicting priorities how does an organization successfully fill the role of the Reliability Engineer? We will explore some tools that allow the Reliability Engineer to be more time effective. We will also discuss potential organizational strategies that can allow dedicated reliability analyses to take place.
Paper 2
ArcelorMittal Tubular Products’ Journey to Operational Excellence: How Two Plants with Different Business Challenges Adopt Optimized Asset Performance as a Common Strategy by Dave Armstrong, ArcelorMittal Tubular Products / Al Weber, Ivara Corporation
Whether you are experiencing dramatic market growth or slowing market demand, ensuring the optimized performance of your assets is a powerful and effective business strategy that drives operational excellence. Attend this session and learn how one company adopted improved equipment performance and reliability as a common business strategy at two different plants – each operating in two very different business environments.
ArcelorMittal Tubular Products is one of the largest most diversified mechanical tube manufacturers in the world with 21 plants operating in 11 countries with a capacity of more than 3 million MT annually.
The company’s Shelby, Ohio plant manufactures mechanical tubing for the fluid power industry and is comprised of two 750,000 square foot plants, employing 750 workers. With the dramatic growth in the mechanical tubing market, everything produced at Shelby is sold. In order to keep up with the increasing market demand, equipment was being pushed to its maximum capacity, with some productions lines running 7 days a week, 24 hours a day.
The Woodstock, Ontario plant manufactures automotive tubing and is comprised of a 688,000 square foot facility with 37 processing lines, employing 640. In contrast to the Shelby facility, Woodstock was experiencing a slowdown in the automotive tubing market. As a result, cost effectiveness and ensuring streamlined, efficient operations was critical. Assets had to be available when needed, with no room for downtime or waste.
Shelby’s goal was to increase plant capacity in order to meet market demand, while Woodstock’s goal was to attain lean operations and reduce costs to address reduced demand. In addition, while the facilities had different drivers for change, they also shared several common challenges:
- Highly reactive approach to maintenance
- A culture resistant to change
- Broad based performance issues and unplanned downtime on older assets
- A time-based Preventive Maintenance program not technically validated
- Asset health data residing in separate systems limiting the ability analyze asset performance
- An aging maintenance and operations workforce
- Asset care was the exclusive domain of maintenance with little collaboration with operations
Attend this session and learn how ArcelorMittal Tubular Products adopted the Ivara EXP Enterprise asset performance management software solution to address each plant’s unique business situations as well as their common maintenance challenges. With EXP Enterprise software, both the Woodstock and Shelby plants have adopted a proactive asset care process that has resulted in increased asset availability and reduced downtime.
Paper 3
Improved Reliability at DCP Midstream by Kent Christopherson, DCP Midstream
Over the past six years, DCP Midstream has developed its proactive maintenance program by using & developing new technology and better work processes. This session will discuss the many successes that have come from the use of IR Thermography, Low Band VOC Thermography, IR Lasers, Spectrum Vibration Analysis, Root Cause Failure Analysis, Failure Modes & Effects Analysis and new innovative work processes. The use of the new technologies along with better work processes has delivered higher availability and significant value to the bottom line of the company.
Paper 4
Maintenance and Reliability Indicators in Parenteral Manufacturing Plant by Carlos Velez, Wyeth Pharmaceutical, Carolina P.R.
The development, introduction, utilization, and benefit of a ‘Maintenance & Reliability Indicators System’ (MRIS) in a Pharmaceutical Manufacturing Environment are described in this paper.
The pharmaceutical environment presents unique challenges due to the fact that equipments within controlled environments are generally inaccessible. The controlled environment (aseptic complex) imposed personnel and movement restrictions as well as regulated mechanical interventions. In addition to this, the aseptic areas require that the machines operate at the highest level of cleanliness in order to prevent the contamination of manufactured product.
After a plant shutdown in 2006, production equipment was suffering from excessive downtime. Due to resource limitations, a system of indicators were developed and implemented in order to describe the functionality of the equipment and help sort out the major offenders. The indicators were used to determine where the team’s time needed to be spent in correcting problems. Indicators used include Equipment downtime, Mean time Between Failure (MTBF), Mean Time to Repair (MTTR) and Availability.
The use of indicators as a system gives concrete data with which the Maintenance & Reliability Engineers can recognize and determine the critical major offenders. Equipment Downtime data is collected routinely and the MTTR, MTBF and Availability for each equipment is calculated on a regular basis to facilitate equipment performance analysis and business decision-making.
Through the use of the indicator system, projects were put in place to correct recurring faults and maintenance strategies were devised to prevent common mistakes from occurring. The results have been encouraging with equipment downtime reduced from 20% down to 5%. Manufacturing Operations have been able to supply quantities of pharmaceutical product due to the limited interruptions to their equipment increasing their output by 20% in the aseptic areas.
Paper 5
The Link Between Equipment Reliability and Personnel Reliability by Ken Reed, System Improvements, Inc.
We have seen numerous studies discussing the benefits of determining and tracking equipment reliability metrics. These metrics are used to pinpoint inefficiencies in our maintenance processes, direct resources to problem areas, finalize budget allocations, and benchmark our company against industry leaders. With world competition making profit margins slim, these analyses are becoming more and more crucial to the business plan.
Like all statistics, this data is only useful over a specific range of assumptions. These assumptions can include such things as current and future energy costs, equipment depreciation, equipment downtime and planned upkeep periods, and cost per unit production. It is understood that an inaccuracy in any of these assumptions will cause associated inaccuracies in the outcomes of the analyses. For example, the decision to replace a pump with a more efficient design can be rationalized by offsetting the increased cost of the newer design with the cost savings due to lower energy usage. The payback time for this offset is dependent on accurate estimates of the future energy costs expected during the life of the equipment.
However, some basic assumptions are often missing when a company assesses the reliability of its equipment. When a compressor bearing fails, we can look at oil samples to determine what components are failing, vibration measurements to determine failure modes, and maintenance records to determine run hours. However, why did the bearing fail? Was the equipment started correctly? Was it shut down correctly? Was the maintenance performed correctly? This information is rarely reflected in the statistics.
In this paper, we will analyze the methods in place to detect and correct equipment malfunctions. We will concentrate on the failure analysis process, with a particular focus on proper methods of drilling down to the actual cause of the equipment failure. Case studies will be provided to show common shortcomings of equipment troubleshooting followed by a case study using Equifactor® Equipment Troubleshooting techniques combined with the TapRooT® Root Cause Analysis system to find the real reasons and root causes for equipment and component downtime and failures.
Paper 6
Meeting Maintenance Cost Reductions Through Technology by Michael Liegel, Fluor
In today’s economic climate, cost pressures are commonplace, and the Maintenance arena is no different. As companies strive to maximize shareholder value, the Maintenance department is increasingly under focus. A large Fluor Client with 12 different sites, tasked Fluor with a 10% cost reduction, no small initiative and creativity was essential. Technology was the driving force to achieve this goal and through collaboration with the Client, the cost challenge was achieved. Significant modifications to the maintenance work processes were undertaken to enable efficiencies through technological developments. The largest contributor was the design, development, and successful implementation of handheld PDA’s for the maintenance work force. Moving to an electronic dispatch process, created a paperless environment where the schedulers no longer had to contend with huge volumes of paper work orders, and allowed them more time to concentrate on their primary function. Technicians were no longer waiting for their daily work assignments, as they were electronically delivered to their PDA. The system allowed future assignments to be scheduled in advance and only appear on the device when scheduled, thus maximizing schedules, whilst not appearing to overburden maintenance technicians.
The PDA devices allow maintenance technicians to seamlessly upload and download their work orders to the CMMS, through a cradle with internet access or a wireless connection. Work order information on the device includes detailed work instructions, location, and equipment information to allow the maintenance technician to complete the work efficiently the first time. All logging on time, comments, and coding is completed electronically by the technician, and this is uploaded to the CMMS with the touch of a button.
Management and setup of the CMMS databases across the sites was streamlined to include a Master Database capable of updating settings to the 11 different child databases. These initiatives also allowed resource allocation sharing across multiple sites, by moving from a site centric basis to an account centric basis. This was not limited to the maintenance function, but included the Finance, Engineering, and Procurement functions. Utilizing the new approach, annual cost savings of over $500,000 were realized, greatly assisting in reaching the 10% cost reduction target.
Paper 7
The Statistical Outliers are in Control of Asset Management by Tom Carrol, NetJets, Inc.
Some of the key components in asset management involve ensuring the assets are performing as intended and expected, effectively resolving maintenance issues that inevitably arise, and minimizing the cost of supporting that maintenance. The performance and material support of these assets are generally predicted by a statistical model, which sets the course for resource planning and provisioning. Traditionally, the statistical outliers in these models are ignored in order to focus on the majority of the general population. However, it is these outliers that have the greatest impact on how effectively the assets are managed.
The statistical outliers are similar to the rudder of a ship, in that the rudder is a relatively small part of the vessel, and outliers are a minor subset of the general population. Their effect on asset management is also remarkably similar – as the rudder determines the ship’s course and control, these aberrant performers have a controlling effect on the efficiency and success of the management process.
Statistical outliers of the asset population typically fall into four categories: premature removal (infant mortality), production flaws (bad from birth), wear out (geriatric) or rogue (chronic) components. While the first three are relatively easy to identify and resolve, and have a minor impact on asset management process, the last category is extremely difficult to recognize, even more of a challenge to control, and has an exponentially greater impact. This is especially true with spare parts that are bench checked, repaired and reintroduced to service.
Despite the incorporation of all the controls and processes in traditional asset management strategies, failure to focus on the identification and resolution of statistical outliers in the asset pool will have the same effect as a broken rudder on a ship – even though a lot of effort and precision is applied to control the direction, the result will be ineffective and unpredictable.
This presentation will describe the development of these statistical outliers, define a Darwinian “natural selection” process that acts as a catalyst to facilitate their control of the asset management process, focus on some of the resulting negative effects, and outline the means necessary to control them.
Paper 8
BPXC Sales Gas Plant (SGP) Maintenance Plan Optimization and Implementation of a Performance Based Maintenance Contract by Wolman Cardenas, WG Colombia
The shifting of traditional maintenance department functions to a service center model that manages maintenance activities nowadays is causing many manufacturers to review how maintenance functions are performed at their facilities.
The outsourcing of the maintenance function through the use of Performance-based maintenance contracts has become the preferred solution for many companies as this allows them to focus on their core business whilst ensuring that the maintenance responsibilities are outsourced to organizations with the required expertise and with common goals and objectives.
This paper demonstrates that the transition of a maintenance contract based simply on supply of personnel (body shop) to a one based on performance is feasible only by changing the maintenance strategy from one based on vendor recommendations to one based on RCM principles. Furthermore new strategy will require the identification and calculation of maintenance indicators which will be the basis of the new performance based contract.
Cusiana’s Sales Gas Plant, propriety of BPXC, is the main source of gas for Colombia, with a nominal capacity of 200MMSCFD. Its initial maintenance strategy was mainly based on vendor recommendations for new machinery. After two years of operation a strategy review took place, based on the Common Maintenance Strategy of BP (founded on RCM principles), the experience gained by the operations and maintenance personnel and the availability of new simulation software (such as AVSIM+, based on Montecarlo Simulation). The optimization process and its results are described this paper, highlighting the experiences of migrating from the previous body-shop style contract to a performance-based one. The paper also provides a detailed study of the maintenance strategy optimization process and an overview of the execution of chronic failures root cause analysis used to improve the performance of the Sales Gas Plant critical equipment based on the critical failure modes.
Paper 9
Improving Equipment Monitoring: Application of Wireless Vibration Sensors by Brandon Rasmussen, Kurz Technical Services, Inc.
Wireless technology provides the ability to monitor hard to access equipment and to economically add instrumentation to improve monitoring capabilities. The majority of critical rotating machinery is monitored on a periodic basis using vibration sensors and handheld devices to collect and analyze the data. This raises two issues which can be efficiently remedied using wireless capable devices and advanced empirical modeling. The first issue is the time required to perform periodic rounds and the possibility for degradation to occur between analyses. The second is the independent analysis of vibration data and related process parameters. Equipment degradation will often affect both standard process variables and vibration data. Empirical modeling techniques can be used to combine vibration data and process variables into an overall diagnostic model for rotating machinery.
This work intends to combine different types of data sources (high frequency and low frequency), implement a wireless sensor network, integrate the wireless data with the existing plant historian, and to construct and evaluate empirical models to monitor the combined data and produce concise assessments of the health of the monitored equipment. An overview is presented below in Figure 1. The focus of the presentation will be on the implementation and use of wireless sensors. There are a variety of other aspects of the overall project, but the acquisition and display of the wireless data is most relevant to the maintenance community.
Figure 1: Integrated wireless monitoring
Paper 10
Turning Corporate Asset Management into Real Earnings Per Share Growth by Robert DiStefano, MRG
While Corporate Asset Management (CAM) has been a hot topic amongst global companies for the past decade, the demands of the transformational requirements (culturally, technologically, procedurally and philosophically), compounded with the time to achieve, often mask or even prohibit the visibility of bottom line financial benefits. For example, once approval for a CMMS system is given, and taking into account the time to implement, the all too often oversight of the implementation plan to address data quality when doing data conversions, and personnel “brain drain,” results in the business case benefits associated with the project having already been removed from the ongoing budgets. Years later, one doesn’t clearly “see” the bottom line impact the new system produced without serious financial comparative analysis.
The question becomes, “How do we implement a Corporate Asset Management strategy in a pragmatic way so that real business value (Earnings Per Share - EPS) can be seen at each phase of the transformation?” A focused look at the decomposed ROA (Return on Assets) of the company can help us in this quest. That is, analysis of the company’s Revenue, Costs, Fixed Assets and Current Assets (with relevant benchmarking to their peers) can quickly identify which leg of the CAM stool is shorter than the rest (supply chain, reliability or marketing). Experience shows that rarely do companies have sufficient and accurate data to do such an analysis, thus giving insight into where they need to begin – standardizing and normalizing their material and asset data! This foundational asset (yes, data is an asset), even without additional investment in process and technology upgrades and improvements, can result in reduced inventory, increased productivity and increased throughput, thus providing positive impact to net income and total assets driving ROA improvements in months, not years.
Leveraging this data into managerial information, as well as strong market support for a company’s product and likely investments already made in supply chain management (thus largely addressing the inventory or current asset component of ROA), a renewed and focused analysis of the net income can be launched. What is limiting the asset efficiency of the company? Why is throughput less than their peers? What is the percentage of unplanned versus planned downtime? What improvement in throughout or income can be attained by reducing unplanned downtime by as little as 5%? 10%? Remember, reduced unplanned downtime translates into immediate ROA gains!
Paper 11
Implementation of a Coal Pulverizer Maintenance Improvement Plan for Fossil Plant Assets by Michael Cook, Talecris Biotherapeutics
This paper describes the steps taken to implement an improvement program for coal pulverizer maintenance at multiple fossil sites. The program steps were designed and executed by a corporate pulverizer team tasked to define the action items needed to improve pulverizer maintenance methods by optimizing and standardizing maintenance practices. The main improvements include changes to the spare parts system, the maintenance templates which describe the parts scope, the written procedures that describes the work scope, and the methods used to plan and scheduling these actions.
The Progress Energy Maintenance Council identified coal pulverizer maintenance related improvements as having a high potential for return. The Pulverizer team was tasked to define the steps to improve pulverizer maintenance methodology by optimizing and standardizing maintenance practices.
This paper describes the steps taken to make improvements to numerous elements of the maintenance program designed for a fleet of 130 individual pulverizers on twenty-three units at nine fossil plants. This includes nineteen different pulverizer models from five different manufacturers; Babcock and Wilcox, Foster Wheeler, CE/Alstom, Riley and ABB.
Coal pulverizers receive coal either directly from the coal pile or from a crusher unit in the 1” to 1.5” diameter range. The pulverizers convert these large nuggets to a highly combustible powder form. Providing properly sized particles allows for the most efficient heat transfer and minimizes negative environmental and operational impacts.
The recommendations from the Maintenance Council were to implement an initiative that was specific, measurable, achievable, realistic and timely. The potential areas of improvement were identified by the Pulverizer Team and presented to the Maintenance Council.
- Safety
- Planning & Scheduling
- Predictive Maintenance
- Work procedures
- Cost tracking
- Inventory
- Engineering upgrades
- Use of vendors
- Knowledge capture
- Tools and rigging
- Parts procurement
- Spares and inventory
- Information sharing
- Goals & Metrics
- Use of in-house and outside resources
Based on a brief review of the potential for return on investment and the historical need for improvement, the Maintenance Council screened the potential areas of improvement and decided that the primary focus of the Pulverizer Initiative would be to accomplish the following goals:
- Determine individualized maintenance templates for all work performed on pulverizers
- Develop parts templates with a common format for all pulverizers related maintenance
- Generated detailed work instructions for all major overhaul maintenance tasks on pulverizers
- Developed a common scheduling methods that will allow for fleet wide resource management
- Negotiate favorable contracts with all major vendors
The benefits anticipated from these activities were improved budgeting and planning for pulverizer maintenance activities, reduced capital costs through better stock management, reduced maintenance costs, and optimized turnaround time for overhauls.
The development of the model program was an iterative task that involved adopting best practices from existing plant maintenance methods, pulverizer manufacturers, and program elements already successfully deployed in corporate programs in non-pulverizer applications. These elements were combined to create the basis of the maintenance function for all pulverizer related activities.
Paper 12
Using Filter Debris Analysis To Detect Abnormal Wear in Industrial Equipment by Michael Barrett, Insight Services / Dr. Karen Cassidy, GasTOPS, Inc.
Advanced warning of abnormal wear in critical operational assets provides decision makers valuable insight on the health of their rotating equipment. Armed with this information, the uncertainty behind maintenance decisions is eliminated enabling the proper scheduling of maintenance actions, ultimately, saving money by avoiding operational upsets and minimizing maintenance costs. With today’s emphasis on oil cleanliness companies are turning to finer filtration to extend the life of their most critical rotating equipment. Consequently, more debris is captured in filters and less remains in the oil. Wear debris analysis through oil analysis is no longer enough to predict impending failure. The next generation of wear debris analysis requires Filter Debris Analysis (FDA) to uncover the wealth of information buried in your filter and gain a comprehensive assessment of machine wear. This paper will explore the success of Filter Debris Analysis in the U.S. Navy and how the technique is now being delivered to the industrial market.
Paper 13
Is Your Control Room Data What You Think It Is? by Ray Beebe, Monash University
The investigation and diagnosis of plant problems is an important part of the maintenance and reliability engineering function. The techniques used often relate closely to those used in condition monitoring, and therefore tests that require special instrument arrangements or dedicated instruments are often required. Savings in effort and time are possible if permanently installed instrumentation is available in the control room with displays and recording. This is further facilitated with computer-based systems, especially if remotely accessible. These have an apparent authority that may imply greater accuracy than is justified, as the data displayed and/or recorded is only as accurate as the initiating element and its placement. This paper has several case studies that illustrate some key points for maintainers and designers.
Paper 14
Advanced Vibration Analysis Applied to Wind Turbine Gear Boxes by Dr. Stewart Bowers, Emerson Process Management
The purpose of this presentation is 1) to instill awareness to the attendees of the benefits of both macroscopic (low frequency) and microscopic (high frequency) vibration analysis for early fault detection, fault location, and severity assessment, 2) importance for the identification of all possible periodic faults associated with shaft speeds, gearing, and bearings, and 3) importance of a seldom used analysis tool, Autocorrelation Function Coefficient, for the identification and severity assessment of faults.
The “purpose” will be accomplished through case studies from two 1.5 MW wind turbine generators. The first, Generator A, utilizes data from the gearbox from a live generator supplying power to the electrical grid. The second, Generator B, utilizes data from a gearbox on a test stand undergoing endurance testing. One of the faults was a ring gear-meshing fault which was present at the very beginning of the endurance test cycle.
There are several moving parts located in the Nacelle housing the wind turbine machine train, which will benefit from an active vibration-monitoring program. The most difficult (for monitoring) component in the machine train is the gearbox. The gearboxes used in this study consisted of a planetary section driving a spur/helical section. The two sections are housed in a single enclosure with the results of a relatively small compact gearbox. The input is a three bladed fan driving the carrier of the planetary section (typically in the 20 RPM range). The output of the spur/helical section is directly coupled to the generator. The difficulty of vibration analysis lies in the detection of faults coupled with identification of the location as well as the severity of the fault.
The faults represented in the selected case studies consist of a ring gear meshing fault, a planetary gear-meshing fault, an eccentric bull gear (gear, bent shaft, or gear alignment) fault, excitation of probable torsion resonance, and an early stage-bearing fault. The analysis tools employed consisted of 1) normal acceleration spectral data computed from a band (frequency) limited time waveform, 2) time waveform consisting of peak values (PeakVue™) from the high frequency data using a time compression methodology, 3) spectral data computed from the compressed peak value waveform, and 4) autocorrelation coefficient function computed from the peak value waveform. The case studies will demonstrate the importance of each analysis tool for fault detection, location, and severity assessment.
Paper 15
The Wireless Revolution by Mark Vowell, Commtest
Permanently-mounted remote monitoring systems have long shared one element in common: a wired, physical connection between the analysis software running on a personal computer, the data collection unit and the remotely-mounted sensors. Installation requires extensive cabling, with its associated cost in materials and time, plus the ongoing maintenance due to electrical and mechanical interference, physical wear and damage.
Wireless connections using secure wireless protocols are becoming increasingly desirable; eliminating much of the installation costs, allowing access to previously inaccessible sites and providing an unmatched level of installation flexibility. However, wireless solutions also present their own problems. This paper presents typical problems encountered when choosing to join the wireless revolution along with some innovative solutions.
The presentation will also present several recent installations of Commtest’s wireless devices, recounting specific applications during the testing phase of the product. Benefits of using wireless sensors at these test sites will be discussed, as will the advantages of having wireless capabilities for the applications at hand.
Paper 16
PANEL DISCUSSION: How Do You Determine How Well Your Company is Doing in Maintenance and Reliability? Led by Tim Holmes, DuPont
MRC members all agree that Maintenance and Reliability are strategic enablers to the financial success of any company. The question is, "How do you determine how well your company is doing in Maintenance and Reliability?" Six Sigma tells us that there are at least two approaches:
- Measure the inputs - "How well are we implementing known best practices?"
- Measure the outputs - "How well are we doing based upon our functional and financial metrics?"
This panel discussion, with questions and answers following, will present How Several MRC Member Organizations Determine how they're performing in Maintenance and Reliability.
Paper 17
Does it Rotate? Do You Want to Cut Costs?: Reducing Energy and Maintenance Costs with Helical Gearing and Premium Efficient Motor Solutions by Mike Stoneburner, Baldor Dodge Reliance
Over 25% of all electricity used in the U.S. runs through our types of electric motors(1). Premium Efficient motors, combined with the newer style of gearing…helical… can significantly reduce plant operating costs, and maintenance costs, if specified correctly.
We’d like to present two case studies today, from our collective 300 years of experience as a company, that illustrate how good specification of power transmission applications can reduce maintenance and energy costs, while improving safety.
At Baldor Electric Company, our mission is to have our customers define us to be the best marketers, designers and manufacturers of industrial electric motors, power transmission products, drives and generators. We are the #1 electric motor company in North America (by revenues). Our Dodge product line of speed reducers, bearings and power transmission components is number one in several market classes as well. We have a combined track record of over 300 years of experience as a company in the Food, Aggregate, Cement, Unit Handling, Power Generation, Paper, Petro Chemical, Fluid Handling, HVAC and Mining industries.
We’d like to share our Best Practice Case Studies found in these industries with the MARCON audience to help them:
- Reduce Maintenance Costs (Case Study #1)
- Improve Safety (Case Study #1)
- Reduce the number of suppliers and parts for common applications (Case Study #1)
- Reduce Energy costs with Helical Gearing & Premium Efficient Motors (Case Study #2)
- Map Maintenance cost savings delivered with TCO Tools (Case Study #2)
Case Study #1
Theme: Improve safety, reduce inventory, reduce number of suppliers: The beltless advantage. Ease of access to repair/replace, the C-face advantage.
Pug Mill: A pugmill or pug mill is a machine in which materials are simultaneously ground and mixed with a liquid. Industrial applications are found in pottery, bricks, cement and some parts of the concrete and asphalt mixing processes. (Source: wikipedia)
One large (120') conveyor is fed by multiple feeder belts. Each feeder supplies the large conveyor with different materials. The large conveyor conveys all this material to a Pug Mill. The Pug Mill collects ingredients, mixes ingredients, and distributes finished products (you will hear terms like 57's, 10's, etc.) to dump trucks all day long. The Pug Mill was upgrade recently with two Quantis ILH gearboxes and Paraflex couplings. This setup replaced a series of belt drives, chain drives, and exposed gearing. The Maintenance Buyer says it has been one of their best purchases of the year.
Case Study #2
Theme: Reducing a food company’s energy costs with Helical Gearing and Premium Efficient motor combination, mapping the cost savings with TCO tools.
The following case study is quoted with permission from the book Value Merchants, Anderson et al, HBSP, November 2007.
Early last year, a condiment producer hastily summoned Baldor sales representative, Mr. Jeff Policicchio, to participate in a “Continuous Improvement Conference” at one of its major plant sites. Facing considerable pressure from Wal-Mart to lower its condiment prices, the producer decided to invite its incumbent suppliers as well as competing suppliers to a meeting designed to find ways to dramatically reduce its operating costs. Along with competing supplier sales reps, Jeff was given full access to the plant and its personnel for one full day.
From discussions with plant personnel, Jeff quickly learned that a major and recurring problem stemmed from lost production and downtime attributable to poorly performing pumps on 32 huge condiment-storage tanks. Using Baldor’s TCO Toolbox®, an interactive laptop software program, Jeff generated a list of probing questions designed to gather data associated with pump usage. Through extensive interviews with the plant engineer, maintenance manager, and purchasing manager, Jeff gathered relevant cost and usage data and entered it into his laptop’s TCO Toolbox program. Based upon an assessment of data, Jeff was then able to construct a “pump solution” or what the trade calls a “screw-drive” comprised of a Reliance XE motor, a DODGE Quantis gear reducer, and a Reliance variable frequency drive.
The next day, Jeff and his competitors were called back to the plant and given one hour to prepare a solution proposal and present it to plant management. Again, Jeff used his TCO Toolbox program to generate a value assessment report, craft a value proposition, and prepare a set of slides for his presentation. Following the presentations, Jeff learned that he was the only one to use a value assessment tool to demonstrate tangible cost savings attributable to his proposed solution. Everyone else made fuzzy promises about possible benefits. Stated simply, Jeff’s value proposition was, “Through this Baldor pump-solution, your company will save at least $16,268 per pump (on up to 32 pumps) relative to our best competitor’s solution through the elimination of most downtime, reduced administrative costs associated with procurement, and lower spending on repair parts.” Plant management was so impressed with Jeff’s value proposition that they immediately purchased one pump-solution for a trial examination. After a trial period, plant managers audited the Baldor solution’s performance and discovered it to be even better than predicted. Based upon these findings, they placed orders for the remaining pumps. They will be installed as the existing pumps wear out.
Paper 18
Application of Data-Based Performance Monitoring Methods to Process Units of Fossil Power Plants by Dr. Belle Upadhyaya & Fan Li, University of Tennessee College of Engineering
Recently, fossil power plants have developed the capability acquiring historic data, thanks to the Distributed Control System (DCS) technology. Process variables are continuously stored in databases at discrete time intervals. This explosive growth in data and databases in power plants has generated an urgent need for new techniques and tools that can intelligently and automatically transform the process data into useful equipment health information and maintenance knowledge. Consequently, data mining has become an important support technology for plant operation and maintenance engineers.
Data mining is a process that employs a variety of data analysis tools to discover patterns and relationships in data and to use them in decision the making process. However, it does not evaluate the patterns for performance-related information. The patterns uncovered by data mining techniques must be verified for the particular process unit in a fossil power plant. Data mining is usually composed of three steps: 1) Describing the data; 2) Developing a process characterization model; and 3) Testing the model. The focus of the current research includes analyzing historical data obtained from several operating coal-fired units and developing predictive models empirically for various process units such as feedwater heaters and coal pulverizers. A previously developed Anomaly Detection and Isolation (ADI) module is applied to these systems. The idea is to use various data mining techniques to characterize interrelationships among a multitude of process variables of both coal pulverizers and feedwater heater units used in fossil power plants. Residual sequences are then calculated by subtracting model estimated values from actual measurements. The residual values and their variations from allowable deviations are indicative of possible anomalies. Also, different failure modes may be distinguished based on patterns of residuals, each of which is unique to a given failure mode. Expert knowledge and multiple models are also used in this paper to complement the anomaly isolation task. A schematic of the ADI module is given in Figure 2, where it is applied to a pulverizer system in order to monitor system degradations. These may include feeder clogging, pulverizer clogging, sensor faults, etc. However, the flow of information applies to any process unit or a larger system.
Figure 2. Flow Diagram of Anomaly Detection and Isolation (ADI) Module.
The current results demonstrate the capability of these techniques for modeling long-term process data, characterization of their relationships, and for continuous monitoring of process units. This paper also addresses the issue of avoiding unnecessary maintenance by comparing the diagnostics signatures before and after maintenance. Thus, the plant cost and other maintenance-related problems can be reduced. This is especially critical in plants with a large number of pulverizers or similar process units.
