Archive | Management

70

8:52 pm
March 16, 2017
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Intelligent Water Making Strides towards Predictive Analytics

EXCEL XR metering pumps are designed for the specific chemical pumping requirements of municipal and industrial water treatment.

Last week, I ran across a Smart Water spending forecast from Bluefield Research and this week there’s an interesting post from Jim Gillespie, co-founder of Gray Matter Systems, a system integrator for cloud solutions and predictive analytics. All signs point to an increased spend in this sector for pump and motor sensors, but where will this investment come from?

According to Gillespie and his post on TechCruch, utilities may be able to sell “solutions” to other wastewater operations like the power industry has done. Gillespie cited how the District of Columbia Water and Sewer Authority has commercialized their intellectual property, giving them a new revenue channel. The water district is commercializing their water ammonia versus nitrate algorithm and selling it other treatment plants, according to Gillespie.

>> More || Smart Water Infrastructure Continues to Grow, but Real Challenges Persist

As I noted last week, new investment dollars are hard to come by but there’s are a lot of new use cases in the wastewater space, see below:

Another IIoT development, a new SaaS application that’s set to launch later this month, will calculate wastewater clarifier tank performance — providing quick analysis on a critical step in the wastewater process. The tool, called ClariFind, alerts utilities as they’re getting close to a failure before they experience it. ClariFind will predict when sludge will overflow and be released. This kind of problem causes EPA issues and fines that can run in the millions of dollars. It will also be able to predict a thickening failure, which is when the effluent doesn’t settle correctly and creates a costly sludge blanket in the tank. ClariFind is just one part of a water operations suite of productivity enhancers — solutions as a service.

Read the Full Post on TechCrunch >>


1601Iot_logoFor more IIoT coverage in maintenance and operations, click here! 

75

3:23 pm
March 13, 2017
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Uptime: Improve Equipment Effectiveness

bobmugnewBy Bob Williamson, Contributing Editor

Equipment or, for that matter, any physical asset in our plants and facilities is generally expected to be efficient and effective. In other words, it’s expected to do what it was designed to do under defined operating conditions for specified periods of time. It doesn’t seem like we’re asking too much: RCM (reliability-centered maintenance) focused on improving equipment maintenance with a generally accepted definition of efficiency and effectiveness.

Another, broader perspective of equipment  efficiency and effectiveness, however, also deserves our consideration. This concept was introduced in the 1980s with the concept of    Total Productive Maintenance (TPM).

When TPM hit U.S. shores in the mid to late ‘80s, it was supposed to help us develop organization-wide work cultures for improving equipment effectiveness. The five basic, interdependent “Pillars of TPM” defined principles that made the process work. Coupled with the Theory of Constraints, those principles should have launched a paradigm shift in equipment-performance improvement. In fact, in 1990, I was constantly insisting that TPM would become the predominant equipment-effectiveness strategy of the 21st century. Little did I realize it could become so de-constructed that it would no   longer represent an effective business-improvement process.

Unintended consequences

What changed? TPM’s intent of improving equipment effectiveness devolved into the widespread practice of “operator care.” [Specifically, the Autonomous Maintenance (AM) model for training turned into yet another spin on operator care as being synonymous with TPM.]

As guided by the first Pillar of TPM, the “focused-improvement” principle morphed into a calculated metric of Overall Equipment Effectiveness (OEE). In turn, OEE launched itself into a mega-metric, well beyond its intended use to compare a machine to itself over a period of time.

Of the original five principles (Pillars) of TPM, two were widely embraced by many implementations: operator care/autonomous maintenance and OEE-percentage. Much to my dismay, this reality debunked my previously mentioned “predominant equipment-effectiveness strategy” prediction. Unfortunately, operator care and OEE do not define true TPM.

But it’s not too late to learn from TPM. Given industry’s skilled-worker shortages, demand for significantly improved equipment performance and reliability, and dependence on rapidly growing new technologies, true TPM will be the answer, whether labeled “TPM” or not.

Consider TPM’s expressed aim to improve equipment effectiveness by engaging the entire organization. The first Pillar, “improving equipment effectiveness by eliminating the (six) major losses,” led to a growing list of such losses (or causes of poor performance). The bottom line is that the starting point for TPM-based improvements is the identification of the problems to be eliminated.

Let’s explore those two foundational principles: eliminating the major losses and engaging the entire organization. Improving equipment effectiveness begins and ends with them (and all remaining Pillars of TPM rely on them.)

This diagram helped plant personnel recognize fundamental metrics and measurements for improving bottom-line business performance, as well as deploy plant-floor business-oriented metrics in critical bottleneck areas.

This diagram helped plant personnel recognize fundamental metrics and measurements for improving bottom-line business performance, as well as deploy plant-floor business-oriented metrics in critical bottleneck areas.

What gets measured gets done

Building on the original TPM teachings of the Six Major Losses, let’s jump into what I refer to as “actual equipment losses.” Identifying them is central to improving equipment effectiveness, as well as to getting organizational buy-in and ownership of root causes and sustainable corrective actions.

The accompanying diagram was developed for a client organization to help personnel recognize metrics and measurements that must exist as a foundation for improving bottom-line business performance, as well as help in deploying plant-floor business-oriented metrics in critical bottleneck areas.

Equipment capacity losses

Because the plant-improvement project focused primarily on improving production flow through the manufacturing processes, it was important to understand Equipment Capacity. A fundamental re-definition was necessary since the site had historically linked the concept to standard production rates. Downtime was treated separately, and in very general terms.

Basic equipment capacity was ultimately defined as the design capacity or historical best. Capacity Utilization losses occur when plant leadership makes a conscious decision to not run the equipment. Consider these losses “Planned,” as shown in the diagram.

Equipment utilization losses

Losses occurring when equipment is scheduled to run are categorized in the diagram as Equipment Utilization losses. As shown, some of them, i.e., Unplanned Downtime, Efficiency, and Yield losses, are straightforward. Setup/Changeover losses, though, can be planned or unplanned.

Setup/Changeover losses occur as Planned when those actions are accomplished properly, in the designated timeframe. When setups/changeovers are not completed within the planned timeframe and/or not performed properly, they should be categorized as Unplanned Downtime losses.

While the literature is rich with standard terms for equipment-related losses, there’s a significant advantage in leveraging terminology that is commonly used at a site. The diagram shows a combination of traditional definitions used around the client’s operations, with the addition of new loss descriptions: No or Defective Material, No Operator, and the granularity of three Yield losses.

Material: All bottleneck equipment in the plant depended on material flow to the machine. Unplanned Downtime should be captured whenever material is not available or when it’s damaged or incapable of being run at acceptable rates.

No Operator: Occasionally, some of the plant’s most critical equipment couldn’t be operated due to the absence of a skilled operator. Regardless of the reason, these incidents are logged as a type of Unplanned Downtime: No Operator.

Yield & Waste: Yield losses have a negative impact on planned flow through the equipment and the rest of the plant. The site is now tracking three types of them as part of its flow-improvement project and a separate waste-reduction initiative.

Product Rework losses have a triple impact on the business, i.e., waste of materials, unproductive machine time, and the cost of committing additional labor and machine time to rework the defects or sort the good items from   the bad items.

Despite the amount of actual material waste being created, the plant didn’t historically capture materials lost due to equipment Startups and/or Setups (including Adjustments). This type of loss also contributed to inaccurate inventory downstream, leading to additional small lot re-runs.

Tapping the hidden factory

Plant-floor employees and senior management, and all those in between, should be able to understand the impact of equipment-related losses that have a direct line-of-sight to business goals and objectives.

Tracking Equipment Effectiveness losses and then focusing on eliminating the impact of the “critical few” depends on a collaborative effort that begins with equipment operators. Engaging them and the Operations leadership team in loss-elimination efforts is not only a key component of TPM, it’s an essential element of any reliability-improvement initiative. MT

Bob Williamson, CMRP, CPMM and member of the Institute of Asset Management, is in his fourth decade of focusing on the “people side” of world-class maintenance and reliability in plants and facilities across North America. Contact him at RobertMW2@cs.com.

83

3:16 pm
March 13, 2017
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‘Lean’ Your Way To Workplace Efficiency

03175srandmThe 5S process has proven to be a highly effective organizational tool for modern, Lean work environments. Are your operation’s plant-floor personnel taking full advantage of this methodology?

According to experts in storage, organization, and material-handling solutions at Akron, OH-based Akro-Mils (akro-mils.com), organizations that invest in a 5S process increase productivity, create higher-quality products, and lower operating costs through simple waste removal, visual identification, and efficient use of space. By incorporating a 5S Lean methodology, they note, facilities can:

• improve workflow and productivity
• develop a cleaner, more efficient environment
• create extra workspace
• increase safety
• reduce wasted time and effort
• boost worker morale
• ensure improvements remain intact.

A recent Akro-Mils blog post provided the following refresher on steps in the 5S process, along with some ways this Lean approach can lead to improved workplace efficiency.

— Jane Alexander, Managing Editor

randm1. Sort.

The first step in the 5S Lean methodology is eliminating items that are not needed for the current workflow. This step is crucial to reducing clutter, eliminating outdated or expired materials and supplies, and freeing up valuable real estate in your workspace. A key decision point in this step is determining which items stay and which items go. Unnecessary items are moved out of the workspace and either immediately disposed of or stored offsite and dealt with later.

2. Set in Order.

Frequently used workstation materials and tools should be arranged so that all needed items are readily accessible and easy to find. In this step, the workspace is reorganized and redefined for the most efficient use of space. All tools and supplies are labeled and organized, and a system is implemented to make sure they are always returned to their proper locations.

3. Shine.

When first implementing a 5S Lean process, all work areas receive a thorough cleaning and inspection. A formal cleaning and maintenance schedule is then developed to prevent dirt from accumulating and keep equipment in proper working condition.

4. Standardize.

Benchmarking and evaluation tactics should be used in your 5S Lean process to maintain a consistent approach for carrying out tasks and procedures. For example, standardizing the storage of supplies through color-coding is an effective way to provide helpful, easily recognizable visual indicators throughout an entire facility.

5. Sustain.

The last step is to continue maintaining efficient workflow and productivity with your 5S Lean system. The best way to do that is through education and empowerment of those using the system. Communicating the benefits of an ongoing 5S process will help ensure personnel’s continued adherence to it and, just as important, that there is no falling back into bad habits. Equipping workers with a well-designed 5S checklist does more than merely support the following of those procedures. It’s an effective way to create accountability and keep this valuable process going strong. MT

For more information on 5S and other workplace topics, and to download a copy of the Akro-Mils 5S Procedure Checklist, visit akro-mils.com.

96

3:09 pm
March 13, 2017
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SAP Tips and Tricks: Maintenance Plans — What do all the fields mean?

By Kristina Gordon, DuPont

SAP Maintenance Plans determine how and when a work order or notification will be generated. (Object or notifications will be referred to as objects in this article.) The scheduling parameter settings within the maintenance plan you create dictate these rules. In response to several questions I’ve received about what should be entered and what the value represents, the following screen shot and definitions describe, in detail, the scheduling parameter settings that should be used in a typical maintenance plan. MT

1703rmcsap01p

SF (shift factor) later confirmation:

Based on the percentage entered, this will dictate the next plan date, or due date, of the maintenance plan if an object confirmation has been completed after the original due date.

Example: If the due date for a plan, generated on an object, is Jan. 1, and the maintenance plan is on a 30-day scheduling frequency, however the work and confirmation of that work is not completed until Jan. 15, a 100% late SF will generate the next object on Feb. 15, 30 days after the confirmation. If the SF later confirmation is set at 0%, then the next work order will generate on the scheduling frequency of 30 days without a shift factor calculated in, meaning the work order will generate on Feb. 1.

SF earlier confirmation:

The same rules apply as above, only this formula will calculate based on early confirmation of a work order. If set at 100% and the work is performed 15 days early, the next object will be generated 15 days earlier than the original plan date. If set at 0%, the original plan date will stay the same.

randmTolerance (+):

This determines the difference between the actual completion date and the planned date.

Example: If you set a 20% tolerance on a plan that has a scheduling frequency of 30 days, the calculation the system will use is 30 days x 20% = 6 days. That means you have a 6-day “float” period that is accepted by the system and will not affect scheduling. If you complete the job and confirm the work 6 days early, the plan will not change, i.e., the dates are in the acceptable range.

Tolerance (-):

As in the above example, the parentage calculation applies and will allow a 6-day float after the plan date.

Cycle modification factor:

This calculation is used when implementing maintenance strategies. If you have a cycle duration of 60 days, but want a plan to generate in 90 days, set the cycle modification to 1.5. This will allow the plan to generate an object in 90 days while the other plans on the same strategy will generate in 60 days. The calculation used for this example is 60 days x 1.5 = 90 days.

Factory calendar:

The factory calendar dictates when the system will process scheduling. Factory calendars can be set in the header data of the maintenance plan or at the planning plant item level.

Example: If the factory calendar is set at a 5-day workweek calendar with holidays, object will not accept confirmations on non-working days (this would include weekends and holidays). You will receive a system error message “not a working day.” To avoid this, a factory calendar should be created for maintenance that allows a 7-day, 24-hour working schedule.

Call horizon:

The calculation used in this field will determine how far in advance an object is generated before the plan due date.

Example: On a 30-day plan, if the call horizon is set at 25%, the work order will generate 21 days before the plan due date of the object. It is very important to set your call horizon so that an object is generated so that the job can be planned well in advance of the plan due date.

Scheduling period:

The scheduling period indicates, in days, months, or years, how far in advance you want to see your maintenance calls.

Example: If you set the scheduling period for 365 days, the system will show the calls for that plan for one year in advance. This will help with long-term planning.

Requires confirm:

When you check this powerful box, the system determines when the next object will be generated from the plan. It will only generate when the previous call object has been completed. If you do not check this box, the system will not take into consideration whether the previous object was completed and will generate the next work order on the call date assigned.

Scheduling indicator:

This indicates when to schedule your plan. It will use time, which works in conjunction with the tolerance percentages. Time key date, which will always use the actual date, and factory calendar take into consideration the working days set in the calendar entered.

Kristina Gordon is SAP PM Leader, DuPont Protective Solutions Business, and SAP WMP Champion, Spruance Site, Richmond, VA. If you have SAP questions, send them to editors@maintenancetechnology.com and we’ll forward them to Kristina.

352

2:58 pm
March 13, 2017
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Keep Stored Gear Reducers Service Ready

When gear reducers and other capital spares are improperly prepared for storage, their service readiness can be seriously compromised.

When gear reducers and other capital spares are improperly prepared for storage, their service readiness can be seriously compromised.

Are your statically stored gear reducers service ready? That’s the first of several questions from Dillon Gully of Motion Industries (headquartered in Birmingham, AL, motionindustries.com). He has good reason for asking. In conducting borescope inspections of statically stored internal-gear reducers for customers, Motion Industries personnel discovered as many as one-third of these assets sitting on shelves in a failed state.

Next questions: Are you willing to gamble the OEE (overall equipment effectiveness) and profitability of your facility on gear reducers and, for that matter, other capital spares that might not be service ready? What would you tell your boss if a critical spare were to fail within mere hours? Think this scenario doesn’t apply to you? How can you be sure? Gully offers some advice for achieving peace of mind.

— Jane Alexander, Managing Editor

Effective management of capital spares involves up-front identification of these assets and making sure they are in service-ready condition prior to preparing them for long-term storage. Unfortunately, many operations don’t follow through on this process once purchased units arrive on site. According to Gully, these steps are the only way to support the reliability of stored spares.

Capital spares can be defined as any item that is critical to production, promotes safety, decreases downtime, and/or prevents environmental issues. Gear reducers certainly qualify. The best way of verifying that these assets won’t fail as soon as they’re put into service is to inspect them before they are stored away—perhaps for years. Minimally invasive borescope inspections are a particularly good inspection method.

In a borescope inspection of a gear reducer, a camera scope visually inspects the condition of bearings, gearing, and internal components. The procedure can be accomplished through a plughole, which prevents contamination of an asset, if it is, indeed, ready for service. (Compared to the cost of replacing a failed bearing, costs associated with borescope inspections are also minimal.)

randmStorage planning

While information gleaned from borescope inspections can be used to confirm service readiness—or help identify steps for making a spare service ready—it can also help determine how to prevent these units from improper storage.

Corrosion, i.e., rust and contamination, are two, of many, causes of failure in gear reducers. When borescope inspections identify the presence of these failure modes, steps can be taken to correct them before the equipment is put into storage, as well as prevent those problems from recurring during storage.

Once a plan to prevent failures in stored spares is developed and implemented, it should be consistently followed. Every unit that will be stored, for whatever period of time, should be carefully protected. Preventing rust and contamination is a great start in protecting asset reliability and, thus, ensuring service readiness.

An ongoing process

Keeping stored spares in service-ready condition requires management accountability. Someone must be assigned responsibility for these assets, and expectations should be clear and realistic. It’s the responsibility of that designated person to ensure all spares are properly prepared and maintained. Identifying failed spares and bringing them back to service-ready condition is an ongoing process. As Dillon Gully emphasizes, “It should not be done one time and then forgotten.”

This plan for reliability can lower the probability of failure and bring a welcome degree of certainty regarding your stored gear reducers and other capital spares. MT

Working as an analyst for Motion Industries’ service center in Pensacola, FL, Dillon Gully has been conducting vibration and borescope inspections and managing capital spares for three years. For more information on these topics, visit motionindustries.com or bearings.com.

55

2:53 pm
March 13, 2017
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Mine Business Intelligence From Your CMMS

Car BoomBusiness Intelligence (BI) analysis is crucial to an operation’s success. In short, this analysis is the harnessing of software to mine an organization’s raw data. Analyzing that data through the use of reporting and analytics can support critical business decisions.

In the maintenance world, a computerized maintenance management software (CMMS) system plays a vital role in collecting useful data. Technical experts at Mapcon Technologies Inc. (Johnston, IA, mapcon.com) point to five areas where these systems can help your organization analyze and understand its valuable business intelligence and put it to use.

— Jane Alexander, Managing Editor

Inventory auditing

It’s important for maintenance personnel to know how many parts are needed and when they need to be reordered. By running an inventory usage report within a CMMS, users can find out exactly how many individual parts were used over a specific period of time. Once that information is gathered, a minimum number, or reorder point, of parts can be established to trigger an automatic reorder that, in turn, would be approved and sent to the vendor. This can ensure that stock-outs are no longer a problem and, accordingly, prevent downtime.

randmPredictive analysis

For maintenance departments, being able to predict when equipment will fail is a big deal. A CMMS can determine, based on meter or gauge readings and historical data, when a machine is most likely to break down. Take, for example, a machine that breaks a belt approximately every 1,000 hr. Since a CMMS would display that trend, a technician could set up a preventive–maintenance (PM) task to change the belt every 950 hr. By using a CMMS to predict when the machine will break a belt, downtime can be avoided.

Preventive-maintenance compliance

Since PM information is stored within a CMMS, it is easy to analyze. When reviewing such data, managers can break it down by type of work done, employee, area, or other metrics, and make necessary changes. For example, by determining why certain PMs weren’t completed on time, they could take steps to hire new workers or provide additional training to current employees.

Failure analysis

A CMMS stores an extensive amount of historical data, including repairs, for each piece of equipment in a plant. Therefore, when personnel notice that machines have required numerous repairs, they can analyze stored failure codes to help determine root causes. They can also review CMMS information on when repairs were done, associated downtime, and PM activities, among other things, to devise corrective measures. Say a technician discovers that a machine breaks more belts in the winter due to colder temperatures. With this information, he or she could plan ahead and turn up the heat in the area or order more belts to have on hand during winter months.

HR (human resource) reporting

Reports within a CMMS can be run for things other than maintenance-repair information. Many software programs can run HR-related reports, i.e., an open work order by craft or shift report. This capability allows managers to view the workload according to shift or craft, something that can be beneficial when it comes to hiring decisions. MT

For more information from Mapcon Technologies on this and other CMMS topics, visit mapcon.com.

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