Best Facility Management Software: 2023 Guide

A dark-haired woman looking at two monitors which display a facility management software system. Blue-toned image within a concrete facility
Investing in a new facility management software system is a huge decision, and your organization could experience some level of disruption regarding the new technology—you need to know you’re making the right choice. Some computerized maintenance management system (CMMS) solutions run on preventive maintenance, while others use preventive and predictive maintenance. Some are primarily mobile and SaaS-based, and others are on-premise tools. eMaint, UpKeep, Hippo, FMX, MaintainX—and LLumin’s CMMS+ are all leading CMMS solutions built for mobility and efficiency. Today we’ll look at: LLumin - Their all-in-one CMMS+. eMaint. A leading provider of preventive/predictive maintenance software solutions. UpKeep - An...

Predictive Maintenance Analytics: Improve Efficiency and Reduce Unplanned Downtime

Predictive maintenance analytics is a field of data analytics that assists organizations with their asset maintenance. Through predictive maintenance, organizations can determine when their assets are most likely to fail, optimizing their maintenance tasks and improving their operational efficiency. Predictive maintenance analytics is used throughout industries such as utilities and power, food and beverage, oil and gas, and industrial manufacturing. What Is Predictive Maintenance Analytics? By analyzing data collected from machine-level sensors, predictive maintenance analytics identifies patterns that indicate when a machine is likely to experience a failure. This information can then be used to schedule repairs or replacements before...

Predictive Maintenance & Machine Learning: A Complete Guide

A technician using a tablet within a factory line, presumably in an IoT predictive maintenance machine learning application.
Predictive maintenance technology detects potential equipment failures before they occur, avoiding or minimizing downtime. Machine learning is a powerful tool that analyzes data, learns, and creates increasingly accurate predictions. Together, predictive maintenance and machine learning will improve the reliability of an organization's maintenance and asset management strategy.  Below, we'll discuss the basics of predictive maintenance and machine learning and how each technology enhances the other. Predictive Maintenance and the Intelligent Facility According to Plant Engineering, 40% of today's facilities employ predictive maintenance to reduce downtime, improve ROI, and increase the overall longevity and efficiency of assets. However, over 50% of...

Predictive Maintenance & Life Cycle Management: Get The Most Out Of Your Assets

Facility manager using predictive maintenance software)
Facility success or failure often depends on the ability to minimize costs while maintaining asset performance, and to repair assets quickly when necessary. However, accomplishing this is easier said than done—especially for facilities that attempt to maintain a manual maintenance program. When an asset requires repairs or maintenance, the appropriate personnel must be alerted, replacement components must be ordered (if not already available), and any maintenance work should incur minimal facility or asset downtime. Determining when an asset requires replacement and preparing for that eventuality presents an additional challenge. Asset service life varies considerably based on the application, frequency of...

Predictive Maintenance Technologies

Predictive maintenance surrounded by predictive maintenance technology terms.
According to Deloitte, predictive maintenance lowers maintenance costs by 25%. It further reduces breakdowns by 70% and increases productivity by 25%. So, it’s unsurprising that predictive maintenance technologies are revolutionizing the maintenance management industry. Predictive maintenance is more than just a technology—it’s an entirely new approach to maintenance management. By using machine-level data and predictive analytics, organizations identify potential problems before they occur. Predictive maintenance empowers organizations to engage in proactive maintenance strategies and preventative measures. There are two primary components to predictive maintenance technologies Hardware and sensors used to collect machine-level data. Software – Solutions used to analyze that...

How to Maximize Uptime by Utilizing CMMS Software

Maximize machine uptime by utilizing LLumin’s CMMS+ software
A major goal of industrial facility managers and decision makers is to maximize machine uptime (the average amount of continual running time of machines) and minimize downtime (the average amount of continual time machines are not operating). Production and profits are directly tied to machine uptime. When machines are not operating (downtime), production bottlenecks often occur, which affects production efficiency throughout the facility. Further, production issues slow order fulfillment—which may result in the loss of long-term customers and customer referrals. It is clear that maximizing uptime while limiting downtime is extremely important. However, fully implementing a comprehensive strategy on how...

Mean Time Between Failure (MTBF) And MTTR: A Complete Guide

An operator running CMMS+ software on a machine and calculating MTBF and MTTR.
The metric MTBF is the reliability of a machine. MTTR speaks to logistics required around bringing the asset back up to running status and is a metric that contributes to the criticality and consequence of the asset in an unplanned down state. Machine downtime can result in wasted labor, expensive parts and supplies usage, and loss of production at the least. Simply put, downtime is expensive. In this regard, knowing MTBF and MTTR scores can help us easily manage machine downtime and optimize our processes such that if downtime occurs, the event is as short a time period as possible....

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 leaseAcknowledging what parameters...

Machine downtime truly hurts the food and beverage sector—here’s how to reduce it by 40 percent

Downtime significantly impacts the bottom line in manufacturing—costing companies as much as $260,000 per hour, according to Aberdeen Research. Unplanned downtime is often a result of knowledge gaps involved with machine/shift changeover or machine operations directly. Training and experience significantly improve these areas of operations inefficiencies. Unplanned machine downtime is another culprit. Critical machinery that breaks down or stays down at the wrong time can cause operations downtime that impacts revenue, product quality, and even corporate reputation.    Especially in plants that produce a high volume of goods, continually, and are in regulated industries such as food and beverage. Some major issues...

LLumin’s CEO presents at annual PMMI conference

Recently, LLumin’s CEO, Ed Garibian, presented at the PMMI Annual Meeting in Detroit. Ed focused his presentation on the value of reducing downtime across facilities. Speaking to PMMI’s audience, he discussed how OEMs can integrate learnings from machine data into a machine-as-a-service strategy. This article briefly recaps Ed’s presentation.   Recapping how LLumin established itself LLumin is an enterprise CMMS, asset management, and materials management software solution. LLumin uses machine data to create well-thought-out, predictive products for operations. The purpose of LLumin's product for OEMs is to improve machine performance, maintain ongoing customer relationships, recurring revenue models, and a bridge...