My comment that “technical-based decisions have economic consequences and that economic-based decisions have technical consequences” is often shared during milling and maintenance training presentations. The purpose of this brief article is to expand on the comment and provide insight to the challenges of finding a balance or compromise between technical-based decisions and economic-based decisions at the operative level.
Technical decisions have to do with design, selection, installation, operation, or maintenance of a particular piece of equipment or a complete system. Economic decisions at the plant or operative level often have to do with more short-term – rather than long-term – budget objectives, limitations or constraints, and capital investment.
Both decision types have short-term and long-term implications impacting variable and fixed manufacturing costs and how funds are allocated or spent relative to return on investment. Within each decision basis, an assessment of risk must be made in context of organizational culture and objectives. As can be expected, conflict arises when a decision made is driven predominately by one or the other basis in the face of adversity without consideration of impact. Understanding that one basis impacts the other can lead to better educated decisions and compromises to minimize risk.
Suppose, for example, that a double-high rollstand grinding the same stock on both sides early in the reduction system is not grinding properly, and indications are that the cause is a mechanical issue with the rollstand rather than a roll surface issue.
Can the stand be taken offline without shutting down the entire milling unit? If so, can the rollstand be worked on safely, or will it take longer to make the repair during operation than when the mill is down? Are necessary parts in-house, or is there a significant lead time? Will the feed rate to the mill have to be reduced, or do you elect to keep the same load on the mill and increase grinding load and subsequently roll pressure on other roll pairs of the system? If so, can the roll pairs and respective lifts handle the load, and will the sifter surface available be adequate to handle the load? Can you open the compromised rollstand slightly to decrease grinding pressure to keep the stand in operation while picking up flour production downstream without impacting flour yield or quality?
Every day in a flour milling operation, technical and economic decisions are made and often are opposed diametrically, requiring careful consideration of risk and consequences.
Clearly making the technical decision to shut down the entire mill or reduce capacity has a tremendous economic impact. Downtime impacts both the fixed and variable cost of flour production, just like sitting at the stop sign reduces gas mileage and increases the cost of vehicle operation per unit mile. Taking the rollstand offline or shutting down the mill may be acceptable for a short time; however, there is a risk that the repair takes longer than expected and increases the economic impact. In a 2002 Milling Journal article, the gross margin loss due to unplanned downtime was estimated to be $746 per hour for a 10,000-cwt.-per-day flour mill.
If the assumed safety risk is incorrect and results in injury, the economic and personal impact may be significant, and the judgment to move forward will be called into question. There is little room for taking risks in managing plant operator safety.
Every day in a flour milling operation, technical and economic decisions are made and often are opposed diametrically requiring careful consideration of risk and consequences.
What component parts are necessary or critical to the operation overall and at the systems level, and how is the cost of ownership balanced with plant safety, production schedules, downtime, and product quality? It seems as though there are never enough of the correct parts in stock when a repair is required as a result of a breakdown. Maintaining a large storeroom full of spare parts sounds like a great idea; however, funds tied up in repair parts are not generating a return on investment. Just as you would not buy a spare water heater, furnace, dishwasher, etc. and store them in the basement, a company cannot afford to maintain an excessive investment in parts inventory. The technical decision to have all parts available in the storeroom is not economically feasible, but having critical parts is a good decision. Determining which parts are critical depends on failure rate, impact on production cost, product quality, and lead time, among other considerations.
In our example, it would have been helpful if all sifter surfaces in the system would have remained available. In critical system design, such as primary breaks and head-end reduction systems, one might ask for diverters and/or valves and spouting to allow for taking a rollstand or sifter section offline during operation to facilitate roll changes or other repairs. Such technically based investment may be culled due to cost, an economic decision that one may regret down the road, when more critical and contributing sifter, grinding, or purification capacity cannot be utilized.
Just as you would not buy a spare water heater, furnace, dishwasher, etc. and store them in the basement, a company cannot afford to maintain an excessive investment in parts inventory.
It seems odd that the expense of a duster bypass is approved given the duster’s trivial contribution to yield and flour quality, while such provisions are not made for more expensive and critical pieces of equipment or systems. Given the simplicity of most duster designs, repair and maintenance are conducted adequately so as to prevent unplanned failure and repair, thus eliminating expense and permanent installation of valves, monitors, and spouting which require maintenance and cleaning.
Suppose in our example we elected to continue operation and were fortunate not to have impacted product quality or yield. The risk is that continued operation may result in further rollstand wear and further damage, increasing repair costs, or in the worst case, catastrophic failure resulting in loss of capital and injuring employees. Continued operation of a worn or damaged piece of equipment may result in greater damage and repair expenses. The time to act is upon discovery of potential equipment failure, unless risk assessment suggests otherwise. Only with experience and/or data in hand should repair be delayed, and then only for a limited time. A system must be employed to ensure the issue is addressed and not forgotten.
It is important to remember the integral role a mill operative has in providing input to maintenance regarding machine operation and maintenance needs. The operative’s ongoing machine interaction presents an opportunity to notice changes in sound, temperature, aroma, vibrations, and debris indicating the potential for equipment failure. Changes should not go unreported, and temporary adjustment accommodations and operation should not go unreported. As suggested earlier, the time to act is upon discovery of potential equipment failure, unless risk assessment suggest otherwise.
By the time the operator picks up on the problem, the scope of damage and repair cost has increased beyond that of the original failure due to collateral. In the preceding discussion, an example was provided demonstrating a mill operating situation potentially requiring maintenance intervention. This depends on skillful craft assignment in the facility, as some facilities assign various maintenance activities to both operative and maintenance staff. In either case, it is beneficial to review maintenance strategies that may be taken for a system or facility.
Reactive maintenance is based on the equipment and often deferred until an emergency or breakdown takes the equipment out of service for repair. This type of maintenance may result in critical equipment and system failure, as well as catastrophic collateral damage to the equipment, system, and facility. Where both risk and cost of failure are minimal, such a reactive maintenance approach may be warranted. It is, however, easy to miss or assume a low possibility or probability for a potential failure sequence event leading to catastrophic failure. While a common approach in the 1970s, reactive maintenance is relegated to a lower status within the maintenance strategy hierarchy.
Preventive maintenance is a higher level of maintenance strategy that has developed in the period from 1990 to 2020 and was based first on time-based activities around equipment maintenance to prevent failure and maximize equipment life. Such programs could be managed with a manual database, but as facilities grew and more equipment came off the run-to-failure approach, computer-managed systems grew in popularity.
Determining which parts are critical depends on failure rate, impact on production cost, product quality, and lead time, among other considerations.
In more recent years, preventive maintenance shifted to condition-based maintenance to determine when maintenance intervention is needed. This approach, while not ignoring time-based maintenance, embraced the use of sensors and various devices to monitor equipment performance. Sensors may have included measurements of power consumption or amperage draw; temperature sensing of machine components such as motors, bearings, or gearbox; and product speed, vibration, cycle times, and similar process-specific measures that reflect operational performance or maintenance issues.
Many milling organizations use outside services to conduct electrical, temperature, vibrational, and alignment surveys, in addition to other types of machine system and process analyses. These services often are able to take measurements that would otherwise be risky for untrained in-house staff using costly sensing technologies and analytical methods not readily available in-house.
Expectations for operating the plant at full capacity during budgeted run-time demand an even more advanced maintenance strategy. Predictive maintenance, the highest maintenance strategy level, has the challenge of forecasting performance based on equipment, IoT (Internet of Things), and analysis. Use of outside services – described as part of preventive maintenance – are called in to establish baseline performance of existing equipment and installation of new equipment.
In addition, such services are engaged on both a scheduled basis and an as-needed basis, as these technologies are capable of identifying performance issues in advance of their being identified by either operation or maintenance staff. Performance information collected over the internet provides data for improved risk analysis. Such data and analysis allow corrective actions or intervention to be taken in a planned, coordinated, cost-effective manner, reducing unplanned downtime. With advance notice and knowledge of lead times, spare parts inventory and carrying cost can be minimized, leveraging predictive maintenance.
The gross margin loss due to unplanned downtime was estimated to be $746 per hour for a 10,000-cwt/day flour mill.
Automation has aided milling operation efficiency, product control, and safety in many ways. Data collection capability has been underutilized with respect to operative miller performance and maintenance.
Specifically, in the area of rollermill grinding operation, feed gates are set manually, and feeder roll speed adjustment is controlled electronically by a load sensor above the feeder roll. Failure of the feeder roll, a relatively inexpensive component. can take offline the entire rollstand, a more expensive capital investment.
Feeder roll drive failure has been observed when running the feeder roll out of its range of optimal efficiency and/or with excessive start/stop cycles. Feeder roll data collection and analysis could be used to indicate how well the milling unit is balanced across rolls within and between grinding systems within a mill.
The miller best able to balance the mill as measured by minimal feeder roll speed changes and/or start/stop cycles will have fewer operational issues, improved product uniformity, and diminished equipment wear. Moreover, the data may be used to predict the failure rate for the feeder roll drives.
Take into account your technical or economic biases and bases for decision-making, as those biases impact site economic performance.
Dr. Jeff Gwirtz is CEO of JAG Services, Inc., an international consulting company in Lawrence, KS; 785-341-2371; email@example.com. He also is adjunct professor at the Department of Grain Science and Industry at Kansas State University, Manhattan.