Predict your savings while milling

“A predictive maintenance approach can minimize unscheduled breakdowns of all mechanical equipment in the plant and ensure that repaired equipment is in acceptable mechanical condition. It can also identify machine problems before they become serious. Most mechanical problems can be minimized if they are detected and repaired early. Normal mechanical failure modes degrade at a speed directly proportional to their severity. If the problem is detected early, major repairs can usually be prevented.”

Karan-SinghalKaran Singhal
Milling Technologist
Al-Ghurair Foods-BAE
While slouching world commodity prices have taken their toll on the grain handling and processing industry, there is still strong demand for new projects and expansions in several regions throughout the world, which is further adding competitive pressure on the industry. In such situations cost saving techniques comes as a savior.

Machine manufacturers are doing their bit by constantly improving efficiency and reducing electrical consumption, but as a milling technologist it’s our responsibility to produce finest quality product while taking cost of production under consideration. The industry tends to have cycles that are affected by many factors on macro and micro levels, such one crucial micro level factor which holds great importance but generally gets cornered is Predictive maintenance.

Maintenance cost holds second utmost importance in milling industry. We can broadly classify maintenance into three categories which are illustrated below.

An Introduction to Predictive Maintenance
Predictive maintenance is not a tool, technique or certification. It is a philosophy that uses the equipment’s operating condition to make data-driven decisions and improve quality, productivity and profitability. As millers’ we should have Proactive approach to determine the condition of in-service equipment in order to predict when maintenance should be performed and it should be performed at most minimal cost. This approach promises cost savings over time-based preventive maintenance, because tasks are performed only when warranted.

To some millers, predictive maintenance is monitoring the vibration of motion driven machinery in an attempt to detect incipient problems and to prevent catastrophic failure. To others, it is monitoring the infrared image of electrical switchgear, motors, and other electrical equipment to detect developing problems.

The common premise of predictive maintenance is that regular monitoring of the actual mechanical condition, operating efficiency, and other indicators of the operating condition of machine and process systems will provide the data required to ensure the maximum interval between repairs and minimize the number and cost of unscheduled outages created by machine failures.

Predictive maintenance is much more, however. It is the means of improving productivity, product quality, and overall effectiveness of manufacturing and production plants. Predictive maintenance is just not vibration monitoring or thermal imaging or lubricating oil analysis or any of the other nondestructive testing techniques that are being marketed as predictive maintenance tools.

Predictive maintenance is an attitude that, simply states, the use of actual operating condition of plant equipment and systems to optimize total plant operation. A comprehensive predictive maintenance management program uses the most cost effective tools (e.g., vibration monitoring, thermography, tribology) to obtain the actual operating condition of critical plant systems and based on this actual data schedules all maintenance activities on and as-needed basis. Including predictive maintenance in a comprehensive maintenance management program optimizes the availability of process machinery and greatly reduces the cost of maintenance. It also improves the profitability of manufacturing and production mills.

Predictive maintenance is a condition-driven preventive maintenance program. Instead of relying on industrial or in-plant average-life statistics (i.e., mean-time-to-failure) to schedule maintenance activities, predictive maintenance uses direct monitoring of the mechanical condition, system efficiency, and other indicators to determine the actual mean-time-to-failure or loss of efficiency for each machine and system in the plant. At best, traditional time-driven methods provide a guideline to “normal” Machine life spans. The final decision in preventive or run-to-failure programs on repair or rebuild schedules must be made on the basis of intuition and the personal experience of the miller and maintenance manager.

A predictive maintenance approach can minimize unscheduled breakdowns of all mechanical equipment in the plant and ensure that repaired equipment is in acceptable mechanical condition. It can also identify machine problems before they become serious. Most mechanical problems can be minimized if they are detected and repaired early. Normal mechanical failure modes degrade at a speed directly proportional to their severity. If the problem is detected early, major repairs can usually be prevented.

Five common non-destructive techniques normally used for predictive maintenance management are vibration monitoring, process parameter monitoring, thermography, tribology, and visual inspection. Each technique has a unique data set that assists millers’ and maintenance managers in determining the actual need for maintenance.

Benefits & Advantages of Predictive maintenance
Predictive maintenance is a valuable addition to a comprehensive, total plant maintenance program. Where traditional maintenance management programs rely on routine servicing of all machinery and fast response to unexpected failures, a predictive maintenance program schedules specific maintenance tasks as they are actually required by plant equipment. It cannot eliminate the continued need for either or both of the traditional maintenance programs (i.e., run-to-failure and preventive).

• Predictive maintenance can, however, reduce the number of unexpected failures and provide a more reliable scheduling tool for routine preventive maintenance tasks.
• The foundation of predictive maintenance is regular monitoring of the actual mechanical condition of machines and operating efficiency of process systems will ensure the maximum interval between repairs.
• Minimize the number and cost of unscheduled outages created by machine failures.
• Improve the overall availability of operating plants.

Including predictive maintenance in total-plant management program will optimize the availability of process machinery and greatly reduce the cost of maintenance. As stated earlier in reality, predictive maintenance is a condition-driven preventive maintenance program.

One of the core reasons of implementing Predictive maintenance is as a MAINTENANCE MANAGEMENT TOOL program. The program’s focus should be on following listed criteria
• Eliminating unnecessary downtime, for both scheduled and unscheduled maintenance.
• Eliminating unnecessary preventive & corrective maintenance tasks.
• Extending the useful life of critical systems.
• Reducing the total life-cycle cost of these systems.
• Ensures consistent product quality, due to reduction in unnecessary stoppages.
• Works as assets protection and make provisions for getting Lower insurance rates.
• Helps in obtaining ISO certifications.
• Gives support as a Management Directive for senior level managers to recognize the need to improve the overall reliability of critical plant systems.
• Can be performed when convenient.
• Increases equipment uptime.
• Generates maximum production revenue.
• Standardizes procedures, times, and costs.
• Minimizes parts inventory.
• Cuts overtime due to reduced break-downs.
• Balances workload.
• Reduces need for standby equipment.
• Improves safety and pollution control.
• Facilitates packaging tasks and contracts.
• Schedules resources on hand.
• Stimulates pre-action instead of reaction.
• Promotes cost–benefit optimization.

Disadvantages of Predictive maintenance
• Cost on Predictive maintenance is relatively high on mill as compared to run-to-failure and preventive maintenance. When the cost of implementing a strategy out weights the cost of total benefits received from the strategy than in such scenarios an unique constraint commonly termed as fixing in CATCH 22 is observed and it is a general phenomenon with small mills, which states that to support effective planning and implementing many tools for predictive maintenance, the cost involved in implementing the tool is much more than the actual return from the tool.

• Exposes equipment to possible damage.
• Failures in new parts are more likely if the technician doing the task is less trained for the job to be performed on the machine.
• Uses more spare parts.
• Requires more frequent access to equipment.

Predictive maintenance is an Investment and it focuses on the following points;
• The money involved in the flow.
• The period over which the flow occurs.
• The appropriate cost of money expected over the years.
• Proper training for technicians and analysts. All employees within production and maintenance department must have adequate job skills set.

How to safeguard Catch 22
It is advisable for small mills to opt for out-sourcing Predictive Maintenance to third-party contractual service if they can’t justify the salary of full time in-house team. Contractual service team can undertake these commonly used techniques to support predictive maintenance program.
• Vibration monitoring and analysis by gathering time- domain data with the help of microprocessor based vibration analyzers which automatically converts data using Fast Fourier Transform signature (FFT) to frequency- domain data to set the narrowband of the machine.
• Tribology is a general term that refers to design and operating dynamics of the bearing-lubrication-rotor support structure of machinery. Two primary techniques are being commonly used are Lubricating oil analysis and Wear particle analysis.
• Thermography technique which monitors the condition of machineries, structures and systems, not just electrical equipment. It uses infrared thermometers designed to monitor the emission of infrared energy to determine the operating condition. By detecting thermal anomalies (i.e., areas that are hotter or colder than they should be), an experienced milling technologist can locate and define a multitude of incipient problems within the plant.
• Electrical testing should use traditional methods and must be used in conjunction with vibration analysis to prevent premature failure of electric motors. These tests should include Resistance testing, Megger testing and HiPot testing.
• Visual inspections should be performed by in-house maintenance technicians and millers on daily walk-downs of critical production and manufacturing systems and they should accompany third party out-sourced technicians as well in an attempt to identify potential failures or maintenance-related problems that could impact reliability, product quality, and production costs.

Applications of Predictive maintenance in mills
In mills we have numerous machines working on different types of motion like Rotating, Reciprocating, Oscillating, Eccentric, and Linear hence thereby generating a different vibration profiles from each other. Mathematical these techniques allow us to quantify total displacement caused by all vibrations, to convert the displacement measurements to velocity and to separate this data into its components using FFT analysis, and to determine the amplitudes and phases of these functions. Such quantifications are necessary if we want to isolate and correct abnormal vibrations in machinery.

Millers can make cause and problem matrix log sheets for implementing Predictive maintenance schedule depending upon the size of the mill. For plants more than 350 tpd capacity it is advised to make different log sheets and distribute machines in different classes depending upon equipment’s impact on production capacity, selection of machines in different classes solely depends on the past experience, knowledge and judgment of millers and maintenance managers. These classes are classified in detail are as follows;

• Class I, Essential, machineries must be online for continued plant operation. Loss of any one of these machineries will result in a plant outage and total loss of production. Plant equipment that has excessive repair costs or repair parts lead-time should also be included in the essential classification and some machineries which come under this category are PLC program, Plansifters, Steam boiler (for oats, maize, pulses, feed mill), Centrifugal Fans, Blowers, Dampening system, Compressors, Electrical motors.

• Class II, Critical, machinery would severely limit production capacity. As a thumb rule, loss of critical machinery would reduce production capacity by 30 percent or more. It also includes machines and systems with chronic maintenance histories and also has high repair or replacement costs like Roller mill, Purifiers, Detachers, Bran finishers, Proximity sensors.

• Class III, Serious, machinery includes major plant equipment that does not have a dramatic impact on production but that contributes to maintenance costs. An example of the serious classification would be a redundant system. Because the inline spare could maintain production, loss of one component would not affect production; however, the failure would have a direct impact on maintenance cost. Equipment like air lock couplings, filter diaphragm, Elevator buckets fall under this category.

• Class IV machinery includes other plant equipment that has a proven history of impacting either production or maintenance costs. All equipment in this classification must be evaluated to determine whether routine monitoring is cost effective or not. In some cases, replacement costs are lower than the annual costs required to monitor the machinery in this classification. Products like V-belts, Timing belts, bearings, gears, spouts, and lubrications come under this category.

These were few examples of cause and problem matrix log sheet. Depending upon the need these can be altered as per requirement of millers and maintenance managers.

Below I have showcased the use of different maintenance type with practical results on timing belt.
(A) Run-to-failure maintenance
(B) Preventive maintenance
(C) Predictive maintenance

In short, I would say as a milling technologist our role is not to fix breakdown in record time rather it is to prevent the causes which may result in any type of losses by equipment or system related problems.

In our previous article titled "OPTIMIZATION OF FIXED COSTS IN PLANTS AND SAVING" information is given about "cover story".

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