How IoT-enabled maintenance solutions can elevate the performance of assets in the field, the fleet, and the plant
Since early 2020, organizations that rely on industrial machinery have faced labor shortages, disconnected markets, and disrupted supply chains. We know that the impact is more pronounced for organizations that operate on different machinery and assets. So how can companies move forward?
To thrive for the remainder of 2022, companies should adopt the Internet of Things (IoT)-enabled automation not only as insurance for mitigating future risk—but also as a fundamental business strategy.
Primary issues must be addressed for asset-intensive operations and industries:
- Knowing exactly which type of (and how much) equipment their plants or operations own and lease
- Acknowledging what parameters they need to monitor and measure for each asset type
- Determining how much their equipment costs to operate, mainly whether it costs more to operate than it is worth
- Understanding what remediation, action, or maintenance policies they must put in place to maximize efficiency, quality, and safety
To successfully address these issues, managers should utilize a computerized maintenance management system (CMMS) that uses machine-level data to trigger outcomes. Thereby, managers can pinpoint any machine or asset abnormalities that could impact their plants or operations.
Calculating the quantities of organizations’ highest valued items
Managers must determine the exact capacities, type of equipment, and quantities they have. The ability for organizations to view inventory assets, status, availability, and condition of their assets can get complex when status and condition parameters differ for each type of asset being monitored and managed.
IoT-enabled software provides organizations the solution to monitor and manage the status and availability of their assets. LLumin—one of the leaders in IoT-enabled CMMS, allows managers to create a database of their assets that is easily navigated. This database produces asset master records that capture various characteristics: from assigned locations and fuel types, makes/manufacturers and model VIN numbers, and operational and warranty statuses. Managers will be able to pivot quickly in response to various situations and make critical management decisions.
Enhancing operational efficiency and safety
The determination of operational metrics should accomplish organizations’ goals to meet their operations KPIs, including personnel safety when it comes to plant operations or associated equipment.
Maintaining data accuracy should be considered in order to compare manufacturer and equipment model performance in the same applications and environments (along with the same applications, yet different environments) to decide the ideal solution for unique requirements.
The bottom line?
Managers should strive to manage the following five factors while using a CMMS:
Equipment health. Utilize machine data to determine whether there’s out-of-spec material degradation or wear; create a rules-based outcome to ensure they receive an alarm or alert before the equipment fails. CMMS allows managers to initiate alerts whenever immediate responses are required.
Equipment location. For users with fleets that frequently move, location tracking—via telematics—is vital. If managers are in the mining industry, for example, they can utilize telematics to determine which work cell their equipment has been assigned to within quarries and mines.
Equipment optimization. For team member safety, managers must know whether their equipment has any anomalies. And, if so, they’ll need to solve them as soon as possible so that potential workplace injuries (or worse) are avoided.
Operator behaviors. To ensure equipment remains safe and highly effective for as long as possible, it’s also crucial to optimize operator behavior. Strong CMMS solutions guide operators around pre- and post-use inspections, checklists, and reporting. Plus provides an easy way for operators to alert maintenance personnel if any action must be taken.
Operating efficiencies. Based on historical customer data, LLumin’s real-time machine analytics platform reduces downtime by nearly 40% within the first 12-months of going live. This decline is especially significant, considering that downtime can cost companies as much as $260,000 per hour, according to Aberdeen Research.
LLumin simplifies work completion and decision making, as it provides
- Visibility and understanding of costs,
- History of incidents,
- Past work done – all in a matter of seconds.