The industrial internet of things (IIoT) and Industry 4.0 are already unleashing enormous value in plants around the world. It seems that today’s younger, digital workforce is the energy that propels this change. Past efforts had been sluggish to say the least.

Modern consumer products have put connected devices in our pocket, on our wrist, in our ears, in our car and throughout our home. IoT is projected to deliver between $1.9 and $4.7 trillion of economic value by 2025. The IIoT for asset monitoring is expected to produce $200-$500 billion in economic value by 2025. Condition-based maintenance (CBM), involving real-time sensing and predictive maintenance, is viewed as the “easy win” among all IIoT applications. Many new online sensors are being introduced each year (see Figure 1).

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The sheer number of infographics in the condition monitoring field is staggering; they show up on social media, and in conference presentations, whitepapers, websites and books. Infographics are effective at helping people comprehend difficult concepts that integrate an array of variables and factors.

My soon-to-be-published book, “Inspection 2.0,” covers a host of different condition monitoring methods, including sensory inspections. I was looking for an infographic to illustrate failure modes and detection methods in the time domain for different types of machines and applications but was unable to find a graphic that fit my needs.

Necessity is the mother of invention. Left without choices, I decided to construct my own graphic, naming it Condition Alarm Mapping (CAM). The final product is shown in the figures on the following pages. However, the number of variations and uses of the CAM graphic is extensive and goes far beyond the scope of this article. As an introduction, I can show and describe what it is, why it is needed, and how it is used.

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Inspection, in its most basic form, has been around forever. However, like most things in life, what you get out of an activity depends entirely on what you put in. This column is about radical reinvention of the whole concept of machine inspection. It has little to do with conventional practices of doing daily machine rounds.

With Inspection 2.0, you don’t just “look” at a bearing, seal, coupling or pump. Instead, you “examine” these components with a keen and probing eye. Inspection 2.0 is intense and purposeful. It seeks to penetrate and extract information from what’s been referred to as machine sign language. Inspection 2.0 requires polished linguistic skills to translate this sign language into prescribed activities and instructions that stabilize reliability.

The technologies of machine condition monitoring have been advancing at a near break-neck pace in recent years. These innovations will continue for decades to come. Still, for the vast majority of machines, there is currently no fault-detecting technology more effective than the razor-sharp and relentless focus of a human being.

The potential of a human being as a condition monitoring instrument is enormous. This potential depends on transformation, specifically from the going-through-​the-motions inspections of the past to mission-intensive detective work inspections of the future. That is the essence of Inspection 2.0.

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No warning or short-warning failures are the worst kind. Think of a tire. It can wear out slowly over thousands of driving miles or rupture suddenly, at full highway speed, from a random piece of road debris. You can monitor tread loss over time and conveniently schedule a tire change. Conversely, who could predict the sudden appearance of a sharp piece of iron?

Fault bubbles are sudden-death conditions in waiting. They haven’t ruptured, but they are about to. Similar to a tire, fault bubbles can burst instantly. Unlike the tire, most fault bubbles in industrial machinery can be revealed by condition monitoring, which includes the careful examination by a skilled inspector. Once detected, the root cause can be arrested or at least mitigated.

In past columns, I’ve mentioned the P-F interval. As a review, “P” is the point at which a failure (in progress) is first detected, while “F” is the end point of functional inoperability. Although the P-F interval is a theoretical concept that has useful application, it is rarely applied in real-world machines. This is because the real world comes with many variable events. These events distort the predictability of the P-F interval.

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I have written several articles on inspection recently, as I strongly believe it is foundational to condition monitoring, machine reliability and asset management. My last Machinery Lubrication column introduced the term “Inspection 2.0” to differentiate conventional inspection practices from the intense, probing and purposeful methods needed to optimize benefits. As common as inspection activities may be in any plant, Inspection 2.0 is largely untapped in my opinion. In fact, it is delusional to imagine world-class reliability without the coexistence of world-class inspection.

Inspection 2.0 borrows from many battle-tested philosophies, including the practice of autonomous maintenance advanced by total productive maintenance (TPM) doctrine. However, not detailed in these philosophies is the “how-to” to move an organization past the inspection status quo to the real game-changing opportunity that eludes their view. I plan to address these differences and the “how-to” tactics in several upcoming Machinery Lubrication articles.

This article introduces the concept of machine readiness as a critical enabler to Inspection 2.0. An inspector who is eager to determine the state of machine health – good or bad – needs help from the machine. What hurts, where does it hurt and what are the symptoms of being hurt? Information exchange, like basic communication, is a two-way street. There is a need to enhance the quality of machine-transmitted conditions so the inspector gets a clear and complete picture of the state of the machine’s health.

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The well-known KISS principle (keep it simple stupid) was first coined in the 1960s and began widespread use in the U.S. Navy shortly thereafter. While it started as a design principle for engineers, it has since been applied to any activity or creative endeavor that has had the propensity to become unnecessarily complicated.

What becomes overly complicated also becomes, by default, poorly understood and sparsely used. Conversely, the greater genius in design and engineering lies in achieving the design objective through simplicity and pureness of form.

This can be applied to the world of oil analysis in many ways. Increasingly, oil analysis has become engulfed by complex analytical chemistry and mathematical algorithms. This science is successful when it takes the complicated, such as an array of particles of varying shapes, sizes, textures, colors and compositions, and puts their formation into plain English (e.g., cutting wear on cylinder walls).

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Condition control is defined as the interactive processes of condition monitoring, condition analysis, and condition response. A model is presented which employs the use of expert systems to achieve real-time condition control of a hydraulic system. The approach focuses on the use of fuzzy logic to achieve machine intelligence to monitor and analyze pre-degradation ‘incipient’ failure and impending conditions. Also discussed are the corresponding real-time ‘reactive’ condition responses, coupling system control with condition control.

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Lubrication is an unmistakably integral part of machine reliability. Rotating machines are dependent on lubrication decisions made, such as which lubricant to use, how the lubricant needs to be applied to the tribological zones, and what is done during operations to monitor and control the integrity of these frictional zones.

At the same time, lubrication is too often not top of mind when considering the critical aspects of rotating machines, partly because there is a lack of general understanding of the crucial role the lubricant plays in reliability. But even for those who may understand this, it still is not intuitive to manage these factors carefully. Rather, there are incorrect assumptions that lubrication is straight forward; in other words, simply “just having oil or grease in the machine is largely all that is necessary” is a perspective of many. This, coupled with the fact that lubrication is messy and not as exciting as the many other maintenance tasks, often challenge workforce culture.

As a result, the industry suffers from stagnant practices and lethargic attitudes. Although, the dismal state of an old and generally unexciting field is a huge opportunity in disguise. For plant maintenance personnel that see this opportunity, improvements in lubrication not only help avoid unnecessary costs in repairs and downtime, but also have a huge impact in improving the maintenance culture and creating a foundation for sustainable growth. But what should be the focus for improvement and achieving lubrication excellence?

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There are 8,760 hours in a year. Few plants manage to produce at full capacity for all of those hours. Instead, there are periodic production stoppages due to tooling changes, product changes, scheduled PMs/inspections and unscheduled downtime (reliability issues). Every hour the plant’s assets aren’t utilized is an hour of lost revenue and profits.

Sadly, many plant managers play games with the numbers by ignoring the potential controllability of “scheduled” downtime. Yes, tooling and product changes are unavoidable, but in most other circumstances, there are often practical ways to minimize lost production from scheduled shutdowns.

This can be seen in the difference between typical and top performers in the same industry. For instance, a standard 900-megawatt coal-fired power plant may produce at 86-percent capacity (44 weeks per year), while top performers can exceed 94 percent (48 weeks per year). This is a difference of four weeks of productivity.

Still, no classification of work stoppage causes more agony than unscheduled downtime. The reasons are quite obvious, as a recent online survey of Machinery Lubrication readers discovered. Following is a list of the top reasons unscheduled downtime is so unwelcome:

• Production losses and schedule delays (business interruption)
• Lost revenue and profit (unhappy management/ownership)
• Promised delivery dates are missed (unhappy customers)
• The blame game and damaged relationships between operations and maintenance (morale issues)
• Hurried (botched) repairs cause future problems (cycle of despair)
• Lack of available replacement parts and skilled trades prolongs the downtime interval
• Repairs are at a “cost premium” due to rushed parts purchases, use of overtime labor and collateral damage
• Scheduled “proactive” tasks are replaced by chaotic reactive tasks (leads to future problems)
• Increased work pressure and job stress (job satisfaction issues)
• Safety risks due to rushed work, unskilled work, inferior parts, cutting corners, job stress, etc.

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These days, reliability professionals are faced with diverse options related to technologies and methods to detect, troubleshoot and remediate problems. Figure 1 is a simple example of the available options to collect data and arrive at decisions regarding the health of machinery and machine components.

The logical starting point is always to carefully rank failure modes by both criticality and probability of occurrence. For more information on this topic, see my previous column titled “A New Look at Criticality Analysis for Machinery Lubrication.” This method is known as failure modes and effects analysis (FMEA), and has been extensively documented.

The failure mode ranking sets into motion the critical-path process in reaching optimized decisions related to condition monitoring followed by the prescribed response or remedy. This response should not simply be corrective but also incorporate proactive measures to prevent or restrict recurrence. The emphasis is on optimized decisions and actions.

It’s easy to go cheap (penny wise, pound foolish), but there also can be temptation at the other extreme (a state of reliability excess), often driven by fear of the unknown. The optimum reference state is an activity of seeking balanced decisions. After all, you are not trying to maximize reliability. There is no greater source to find this balance than knowledge and education.

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Inspection 2.0 is rooted in some of the most fundamental and time-honored maintenance principles. One of them is total productive maintenance (TPM). Today, it’s hard to play an active role in the field of maintenance and reliability without encountering and embracing TPM. Honestly, it is delusional to think otherwise.

World-class maintenance organizations understand the intrinsic value of a well-tuned and culture-driven TPM program. World-class TPM programs are fundamentally powered by keen observation. You can’t fix what you can’t see. Therefore, all progress hinges on the power of observation. Allowing you to see is the bedrock. Improve the quality of inspection and, by default, you improve the quality of TPM and all the benefits that TPM seeks to achieve. It’s that simple!

The origin of TPM can be traced back to the Japanese automobile industry in the 1960s. It has many similar elements to the quality movement that was advanced in Japan during the same period. However, it wasn’t until 1988 that the western world learned of TPM when two seminal English texts were published on the subject by Seiichi Nakajima. From that point, TPM spread across the vast global maintenance and reliability landscape.

TPM has similarities and overlapping features with other branded maintenance philosophies, including reliability-centered maintenance (RCM), condition-based maintenance (CBM) and asset management (see Figure 1). However, its strongest difference is the active and responsible role of machine operators and small groups toward maintenance prevention and improved asset utilization.

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Condition monitoring can be easily performed by following a few simple principles. Among these principles include monitoring two sets of conditions:

1. The operating and environmental conditions that precede failure, and
2. Early-stage failure symptoms

Several models are presented that show the benefits of monitoring machine conditions, as well as the consequences of ignoring them. Also discussed is the integration of both proactive and predictive maintenance techniques to extend machine life.

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By some estimates, condition monitoring has been around for more than a century, but it is only within the last 5-10 years (and particularly the last 2 or 3) that interest has been at fever pitch. Dozens, perhaps hundreds, of companies are involved in manufacturing or selling services or equipment for lubricant analysis, wear metals analysis, and vibration analysis, any and all of which can be part of a condition monitoring program. Within the realm of oil analysis itself are many types of tests that can be performed and many instruments that can be used to measure factors of interest. What distinguishes condition monitoring from other uses of oil analysis is not so much the specific techniques used as it is the repeated performance of testing and (most important) the tracking and trending of the results to determine changes in the health of an equipment-lube system over time. Using this information, the practitioner can take proactive measures to avert damage and downtime, saving money, time, and resources.

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It can take just one breakdown of a critical machine to spin an entire plant into an immediate production halt. At this point, it is too late for the plant manager to do anything but call a service technician, then gasp for air while counting the lost production.

Each time a breakdown occurs, a manager vows to begin a rigid maintenance program as soon as time and money permits. But that never happens. Sound familiar?

With all of the attention maintenance advances have received in recent years in the trade press and through technical shows and conferences, it is hard to imagine that any lant would not have implemented an improved maintenance program. Yet advanced maintenance techniques commonly are neglected. Selecting a program that fits the needs of a particular plant environment can be a difficult task.

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When most of us refer to inspection, we are thinking of running machines inspected routinely, say on daily rounds. Unarguably, this type of on-the-run inspection is critical to machine condition monitoring, but other types of inspections are important as well.

At its best, inspection seeks and finds the “precursors” to failure, also known as root causes. This is job one, for sure. Next, inspection must hunt down those elusive incipient failure conditions (the earliest detectable state) that can be as difficult as the sound of a “pin drop” for our senses to detect.

The time horizon when inspection should incur spans from cradle to grave. I’ve emphasized in past columns that Inspection 2.0 is a continuous state of vigilance.

The moment you let your guard down is exactly the time when the enduring Mr. Murphy makes his entrance. To fend off risk and vulnerability, the wise and reliability-intensive organization performs inspection across multiple states.

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Perhaps you’ve heard that machine reliability is everyone’s responsibility. In a general sense, this is very true and needed. We should all keep our eyes alert to issues, large and small. We should foster an inspection and proactive maintenance culture. Inspection is largely about relentless and purposeful sensory observation. Any competent and responsible person near a machine can and should serve as the inspector of the moment.

It’s not just about the machine. There are five inspection operating states, as I discussed in a previous column. Take machine parts, for instance. They frequently are staged in warehouses or on shelves and pallets near operating machines and other active work areas. Sooner or later these components become an integral part of the machines or machine trains where they are intended to be used. Inspection is a cradle-to-grave process, including all the parts that build to a complete and functioning machine or train.

Whatever impaired state or condition the part sustains or is exposed to eventually will be transferred to the operating machine. Even the smallest components that are infected with issues can metastasize and impart hazards and destruction to operating process lines and beyond. It’s not the cost of the repair but rather the cost of lost production that matters, often at many multiples of the repair cost.

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Oil analysis is about surfacing problems that were otherwise hidden from view. We’ve all heard the phrase “if it ain’t broke don’t fix it,” but an important corollary is “if it is broke, fix it fast.” The basic problem with this strategy is not knowing when something is actually broken.

For many organizations, oil analysis offers an effective solution, but it works only if users are literate in its language and apply it effectively. While oil analysis is not a panacea for all machine reliability problems, it does offer many special opportunities. For one, the oil is typically the carrier of both the root cause and symptoms of impending failures.

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A number of months ago I was invited to participate in a planning meeting for re-engineering oil analysis at a large industrial plant. Shortly after taking my seat, introductory remarks were made by the superintendent of maintenance to set the stage for the work ahead. To my surprise we were told to develop a strategy that would allow machine repairs to be carried out on a scheduled basis in-stead of the predominantly unscheduled practices of the past.

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According to major industries throughout the world, it’s time to throw out your old ideas on machine maintenance. The costsaving trend is toward a maintenance program that targets the root causes of machine wear and failure. Predictive and preventive methods are out: pro-active maintenance is in.

Why? Because proactive maintenance methods are currently saving industries of all sizes thousands, even millions of dollars on machine maintenance every year. This concept of saving large amounts on maintenance, however, may be tough for some to grasp.

According to DuPont, “maintenance is the largest single controllable expenditure in a plant: In many companies it often exceeds annual net profit.”‘ Add to this the fact that up to 90% of some companies’ maintenance work involves expensive (and productivity-killing) breakdown repair, and you can easily see the predicament. The problem of costly maintenance has truly reached a serious level, but as some companies have found out, and more come to realize every day, their maintenance costs can be cut drastically by establishing a “proactive” line of defense.

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The field of maintenance technology is going through a revolution of change. Gone are the days when a machine had a predictable service life, after which it was replaced, continuing the cycle. Today, machinery and equipment can be maintained to achieve useful operating Iives many times more attainable than just a few years ago.

The 1980s bore the popular practice of predictive maintenance and condition monitoring to combat rising maintenance costs. In the 1990s, we implement predictive maintenance with greater confidence and precision. These early warnings have proven effective at reducing the magnitude of failure and amount of unscheduled downtime; however, no real progress has been made in reducing frequency. Any maintenance strategy targeting the reduction of failure frequency must address the fundamental causes of failure. Such a strategy of eliminating causes would be “proactive” to failure, not “reactive” to failure.

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