Asset care eats up a lot of spend – from acquiring and storing parts to maintenance. By optimizing these processes with machine health monitoring, manufacturers can save time and money, allowing resources to be allocated toward other aspects of production.

Manufacturing production depends on machines, and keeping these machines running is critical. Traditionally, manufacturers have taken a more preventive than predictive approach: machines are serviced on fixed schedules, whether they need the maintenance or not. This means higher spending because of labor hours allocated to service machines that don’t need it or padding inventory without cause.

When you break down M&R budgets, large portions of expenditures are related to the acquisition and storage of spare parts. Many manufacturers keep these in inventory because calendar-based maintenance dictates when parts should be replaced – even if replacement is not needed. They’re trying to avoid the alternative: overspending up to five times the price trying to get parts on short notice and experiencing more downtime waiting for the parts to arrive with today’s record lead times. Whether spending money to hoard parts or paying more for last-minute parts, both methods are inefficient and harmful to a manufacturer’s bottom line.

What’s more, preventive maintenance focuses your maintenance crews away from higher-level tasks. To keep up with scheduled maintenance, teams are needed on the shop floor to do rounds on each asset, and even more work is needed when machines break down. To save costs on these unnecessary and unexpected expenses, it’s time to focus on asset optimization.

How to Optimize Care Costs

Optimizing care costs means providing the right level of maintenance for every asset, eliminating unnecessary maintenance tasks, and improving maintenance planning. There will always be fixed costs for any production facility, but variable costs can be better managed to ensure manufacturers only spend where it’s really needed – freeing up capital to invest elsewhere.

Optimization doesn’t happen in one day. It depends on the current asset data you have, and it’s an evolutionary process that never truly stops. It’s best to view the process and its benefits in phases that work best for your operations.

For example, you might begin by working to reduce downtime. Once that’s been improved, the next step might be optimizing spare parts inventory before turning a focus toward maintenance schedules.

Working with machine health, Augury’s solutions support your asset optimization goals in a number of ways:

1) Improved Data

With continuous monitoring and advanced AI, Augury’s Machine Health Solutions provide real-time visibility into the health of your critical and supporting equipment. With more insights into machine performance across your production lines, you can make data-driven maintenance decisions and strategies.

2) Optimized Manufacturer Support

Manufacturers don’t need to rely on route- or time-based approaches to avoid equipment malfunction or failure. With machine health, they can gain control of their maintenance schedules, deciding how to spend money and time based on every asset’s condition.

3) Managed Costs

Our insights identify wear and tear patterns on equipment, so you can better forecast the life cycle of parts, making sure you have the right part on hand only when you need it.

4) Maximized Efficiency

Implementing a strategic, autonomous method of machine monitoring frees up time for less tedious work. Using Augury’s insights, technicians are alerted when a machine has problems and notified about how to fix them. They can focus on addressing root causes instead of completing unnecessary routine tasks.

Manufacturers are always seeking ways to improve their means of production. Industrial equipment can be difficult and expensive to procure and maintain. But with a machine health program, you can understand your assets and increase their life cycles, all while reducing M&R costs. Optimizing assets means optimizing business and, ultimately, every aspect of your production line.

Do you want to learn more about how Augury can help you optimize asset care costs? Reach out!

The post 4 Ways Manufacturers Optimize Assets Using Machine Health appeared first on Augury.

Manufacturers know critical assets are vital for continuing operations, but what exactly is asset criticality, how do you differentiate critical from non-critical assets, and how can you use asset criticality scores to drive value?

This article was edited on October 10th, 2023.

How To Identify A Critical Asset

Whenever you put a budget together, there are always those “fixed” expenses that will never go away. For a household budget, mortgage payments, real estate taxes, insurance premiums, and some utilities — though largely variable — would fall within that category. A daily latte from your favorite coffee shop, on the other hand, is more of a discretionary expense that you could do without. Tomorrow, you may decide that it’s more prudent to earmark that money for an actual necessity.

That’s pretty much how to identify critical assets in manufacturing.

Asset criticality refers to how important any asset is to keep business up and running. Whether that means that an asset affects the production line, determines inventory, or represents a large-scale safety hazard should machine health decline, critical equipment analysis provides insights into what’s fixed, variable, and discretionary within operations. You can recognize if a certain piece of equipment is worth the expense — or nothing more than a “nice-to-have.”

“Asset criticality refers to how important any asset is to keep business up and running.“

Critical equipment analysis would, for example, keep you from sinking additional money into machine health sensors on something that won’t give you value long-term. Perhaps after conducting a criticality assessment, you find a redundancy, and something once seen as a critical asset would fall into that discretionary category. The first step in uncovering those redundancies is to analyze each asset and assign it an asset criticality score.

Calculating Asset Criticality Scores

Asset criticality scores ensure that each asset you use is critical to business, and Augury can help with the process. We start with the big picture. Our team looks at each piece of equipment on the production floor in need of monitoring and then applies our equipment criticality assessment criteria to determine its overall value.

For mission-critical assets that directly support safety, compliance, cost control, or operational throughput, Augury installs our full machine health suite of monitoring and analytics tools to drive the most value.

Learn More About Augury’s Machine Health Monitoring Tools.

For medium-critical assets, we can also provide lower-cost support with Machine Health for Supporting Equipment. This autonomous and predictive monitoring enables full coverage — though there can be some overlap with this functionality in monitoring high-criticality assets. Machine health for supportive equipment monitoring is more probability-based. What you use it for will largely depend on in-house tech and knowledge base to monitor that data.

Learn More About Machine Health For Supporting Equipment.

Options For Non-Critical Assets

And when it comes to non-critical assets that are only tangentially related to value-driving objectives (a fire pump, for instance), we can determine whether monitoring such equipment still has the potential to drive some value for the overall production line. If so, we offer lower-level monitoring tools like our handheld vibration-monitoring device.

Unplanned or extended downtime can cost manufacturers millions, if not billions, of dollars. Conducting critical equipment analysis and implementing machine health monitoring tools accordingly can help prevent it.

If you’d like to learn more about our services, watch Augury’s Solutions Architect Brian Richmond discuss the business case for performing a criticality assessment and gain valuable information on how to create your own matrix in our on-demand webinar.

The post How to Identify Critical Assets and Drive Value appeared first on Augury.

Manufacturing costs are on the rise across industries. Meanwhile, many factors contributing to higher expenses are out of a manufacturer’s control. One thing that does remain within your grasp? Production costs. You can drive down production-related expenses such as waste, parts, and downtime by monitoring and responding to machine health in real time.

According to a recent survey by McKinsey, 63% of CPG companies reported a year-over-year increase in manufacturing costs of anywhere from 5% to 20% in 2020. With little control over the costs of raw materials, manufacturing companies in every sector are left with a question of how to reduce production costs in manufacturing by other means.

While manufacturers can certainly try their hand at negotiating with suppliers, the answer may be closer to operations than one might think: machine maintenance and reliability. Thanks to the arrival of AI-driven machine health platforms, like Augury, additional costs associated with repairs can be effectively mitigated if not eliminated by having deep insights into when machines are going to fail and where specifically that failure will take place. 

See how Augury’s machine health monitoring
platform works.

The following are just a few ways Augury’s machine health monitoring platform can help drive down expenses:

1) Predictive Parts Replacement

Traditionally, manufacturers have taken a more reactive than proactive approach to parts replacements and repairs. And when they can’t see a problem coming, they can easily wind up in the unfortunate position of expediting parts shipments. This can increase costs exponentially. In fact, I’ve even had to buy an $8,000 flight just to fly a $1,500 machine part from Germany to avoid an issue for a manufacturer that could have been avoided with machine health monitoring.

With Augury’s machine health monitoring system – made up of machine sensors and AI algorithms to glean insights from machine health data – manufacturers can predict when a machine will need a specific part. They can then take necessary measures to obtain it without incurring additional costs for expediting the process.

What’s more, the machine health data from Augury’s platform is easy to export and share. Therefore, it could be sent to off-site experts who could then walk technicians through tricky repair processes virtually. Instead of paying to fly experts in, you can access them from anywhere in the world at any time.

2) Reducing Waste

Many industries, such as CPG and Pharma, rely on manufacturing through batch production. If a machine failure were to occur during batch production, the manufacturing company would lose an entire batch of goods. For example, say a potato chip company mixes batches of potato chips, but a mixer goes out in the middle of production. The mixer must be replaced, and the entire batch of chips goes to waste. And as waste goes up, so do costs.

With machine health data and insights, however, the manufacturer would know beforehand that the mixer was in poor condition. They could replace the part before putting in the batch, saving themselves from wasting a lot of product.

3) Right-Sizing Storerooms

Many manufacturers still rely too heavily on calendar-based preventive maintenance methods, where equipment care is set at regular intervals according to time or usage. Scheduling this way, however, leaves storerooms stocked with excess parts and pieces, wasting valuable space and driving up costs. Basing maintenance on time or usage can also lead to late or missed maintenance, which could result in costly repairs.

With a data-based machine health monitoring system and meter-based PM schedule instead, manufacturers can know exactly when to repair or replace parts. The approach also offers a fuller understanding of the health and life cycle of equipment. This, in turn, slows down the rate of parts consumption, eliminates the need for excess inventory, and reduces the chances of unplanned downtime. Meanwhile, costs are saved throughout the process.  

4) Eliminating Unplanned Downtime 

On average, manufacturers experience a loss of $260,000 per hour of unplanned machine downtime. Worse yet, 82% of manufacturers run into the problem at least once a year. As indicated earlier, machine health monitoring through data-based systems can make manufacturers aware of the signs that equipment is on the verge of breaking down.

With those insights, manufacturers can plan scheduled shutdowns for machine repairs. And predictive diagnostics and repair insights from Augury’s platform can mean shorter, more efficient planned downtime events. That way, machines get up and running faster, back to producing and generating revenue.

Manufacturing almost any product can be expensive. The costs of raw materials alone are cutting into the profit margins for many manufacturers. And while reducing per-unit costs can come in a variety of forms, the one option under manufacturers’ full control is machine maintenance.  

To learn more about how Augury’s platform provides AI-driven machine health monitoring that can reduce your production costs, get in touch today. 

The post Reduce Manufacturing Production Costs With Machine Health Monitoring appeared first on Augury.

Reducing unplanned downtime can save manufacturers a lot of time and money, but planned downtime can be costly, too. Starting and stopping machines always introduces additional risk for malfunctions and breakdowns, and the longer a machine is down, the more money the company loses while it’s not producing.

Fortunately for manufacturers everywhere, the technology exists today to make planned downtime as quick and efficient as possible so machines can get back up and running faster than ever before. Machine health monitoring systems with advanced AI capabilities like Augury’s can diagnose machines in real time and provide predictive insights about what exactly needs to be fixed and when.

Manufacturers today can work faster and smarter by using machine health insights to reduce planned downtime in two key ways:

1) Prioritizing and Triaging Machine Repairs

Imagine a situation in which you have three different motors of the same size, each with its own unique problem. How do you determine which needs to be repaired or replaced during the next scheduled downtime event?

Without insights into the actual health of the machine, it’s nearly impossible to know which motors are in critical states and which are operating within acceptable parameters. Traditionally, the safest bet might be to just replace all three. But what if two motors could have remained in operation for months without needing a repair, and you needed to replace only one during downtime? You’d have wasted valuable time and money on unnecessary fixes.

With Augury’s machine health monitoring system, however, you can get a much clearer picture of the health of each machine component. Sensors on machines track machine health indicators such as vibration and power usage, and advanced AI algorithms analyze that data to determine diagnostics and predict necessary repairs. Essentially, you get a much better view of what is and is not acceptable in a machine’s current state, enabling you to prioritize repairs and keep downtime to a minimum.

2) Getting People and Parts in Order

Another factor that can prolong machine downtime is not having the right people, parts, or equipment in place before the shutdown. For example, say your on-site technicians begin repairs during scheduled downtime, but they soon discover that they need a technician from the original equipment manufacturer to complete the job. You call the manufacturer only to find out that they can’t make it until tomorrow. So the machine stays down for an extra day, costing the company valuable time and money. Now say the technician arrives only to discover they need a special part or different equipment to make the repair. The downtime event just gets longer and longer.

With a machine health monitoring system, on the other hand, technicians would have a much better idea of exactly what they would need to complete repairs. You could have ordered all necessary parts, acquired all the equipment, and scheduled the downtime event during a time frame of a few hours when all necessary technicians were available. And you’d be back up and running in no time.

3) Optimizing Operational Methodologies

The more you know, the more you can improve your operational flow. By providing the “big picture”, Machine Health data can be used to optimize operational methodologies. For example, if the Machine Health status drops off when a line operates at a certain speed, you can decide to adjust the speed so your assets can perform more efficiently and with less maintenance. In other words, insights can be continually applied to inform and optimize operational decisions — no matter the industry you are operating in. And everyone benefits from optimizing operations. It not only avoids downtime — both planned and unplanned — but also can work to increase safety. Knowledge is power!  

The more you know about the health of your machines, the better you’ll be at fixing them quickly and efficiently. Thanks to Augury’s advanced machine health monitoring system, manufacturers today are able to plan downtime based on more telling insights than ever before.

To learn more about how Augury can help your business reduce downtime, get in touch today.

The post How to Use Machine Health to Reduce Planned Downtime appeared first on Augury.

Roseburg Forest Products owns and manages 600,000 acres of timberland across the U.S. which the company harvests to make plywood, particleboard, engineered wood and many other wood products. Roseburg had a problem: unplanned downtime at its facilities.

Brian Richmond, Regional Reliability Manager at Roseburg, previously served 20 years in the U.S. Navy, where he was a Maintenance and Program Manager for nuclear submarines. He applied everything he had learnt maintaining nuclear submarines to developing a reliability program for Roseburg. The result was that over an eight month period, Roseburg saved $472,000 in downtime costs at a single facility.

Learn Brian’s five best practices to eliminate unplanned in our new infographic.

The post Infographic: 5 Ways to Eliminate Unplanned Downtime appeared first on Augury.