Speed Mean Time to Repair with Analytics and Proactive Alerting

Blog: The Tibco Blog

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Downtime is the top cause of productivity loss in manufacturing. Any time a system, equipment, or process is not running, productivity takes a hit, resulting in lost sales and revenue. According to Aberdeen Research, unplanned downtime in large-scale manufacturing setups can translate to direct losses upward of $260,000 per hour. The impact reaches unprecedented heights when you factor in long-lasting effects like losing employee morale and customer trust. Accelerating Mean Time to Repair (MTTR) through analytical methodologies and proactive alerting can help manufacturers minimize the cost of unplanned downtime. When supported by robust data integration, these systems can detect problems at their earliest stages and sound timely alarms, allowing maintenance to remedy faults before impacting productivity.

Analytics can reveal the root cause and inform measures that prevent a similar failure from happening again, or at the very least, provide a blueprint for quick resolution every time the problem recurs. Read on to uncover the significance of analytics and proactive alerting in manufacturing and how data integration can support both approaches to reduce MTTR.

FMEA, RCFA, and RCA: Leveraging Analytics for Effective Failure Resolution

Failure Mode and Effects Analysis (FMEA), Root Cause Failure Analysis (RCFA), and Root Cause Analysis (RCA) are the three primary analytical methods for fault-finding in manufacturing operations. All approaches aim at anticipating equipment failure by proactively studying all potential causes and digging deep until the specific reason for the fault is revealed and effectively addressed.

Failure Mode and Effects Analysis

FMEA starts by looking into the various parts of a system and how they can break down. It identifies all the possible failure modes—the different ways a system or process can fail—at every part and explores how each mode can affect the system. Then, it provides a maintenance strategy to remedy the failures and arrest their impact before they manifest.

FMEA often succeeds when deployed as a framework for identifying key issues, which are then analyzed intently via RCFA and RCA.

Root Cause Failure Analysis

While FMEA focuses on identifying and solving failure modes, RCFA entails analyzing data to pinpoint the root causes of a specific failure mode and determine the corrective actions required to eliminate or reduce the probability that the root cause will recur.

RCFA is usually considered reactive because it is often deployed after a failure, and the failure mode is known. Nevertheless, when it follows an effective FMEA, it can be a proactive methodology for preventing future issues.

Root Cause Analysis

RCA closely relates to RCFA. However, rather than uncovering a failure’s root cause by analyzing collected data, RCA investigates the various factors that led to the problem, usually by recreating the conditions under which it occurred.

For instance, a pump failure in a chemical plant may be due to a mechanical fault. However, the root cause could be an incompatibility between chemicals or mishandling of chemicals by workers as opposed to actual equipment malfunctions.

Besides analyzing the data collected during the process, a root-cause analysis also considers the operational conditions at the time of failure—power supply, temperature, load, and so on—and digs deep to find what could have caused them to deviate.

Using Analytical Methods with Proactive Alerting Bolsters Problem-solving Capabilities

While FMEA, RCFA, and RCA are powerful issue-resolution procedures, their value becomes more profound when integrated with proactive alerting systems. Knowing immediately when an anomaly occurs in the production process means your technicians can respond quickly and deploy the right methodology to find and fix the fault before it causes downtime.

Proactive alerting systems leverage advanced data and systems integration to provide real-time alerts when an abnormal event occurs. Equipped with automated diagnostic tools, these solutions can determine what has happened without requiring an onsite technician or extensive troubleshooting.

Furthermore, because they connect to all systems along the product chain, they can provide failure mode data alongside the alert, giving your maintenance team a solid starting point for further analysis.

By using proactive alerting and analytical methodologies concurrently, you can effectively predict, identify, respond to, resolve, and prevent problems long before they have a chance to disrupt your production line.

Leveraging Data Integration Technologies for Superior Analytics and Proactive Alerting

Analytics and alerts may seem like all you need to quickly identify and fix failures. However, the effectiveness of the approaches hinges entirely on how you collect data.

Data integration solutions aggregate performance information from various systems to accurately pinpoint a fault and create a complete picture of the problem. Below are three primary ways data integration technology can improve fault-finding outcomes and speed up MTTR.

Comprehensive Data

An integration platform is a readily accessible, intuitive repository of all equipment data. It connects with all your systems, equipment, and processes to collect real-time data and convert it into visual, insightful information. As a result, your staff can get all the data they need to utilize analytical methodologies and form the best conclusions.

Proactive Alerts

Fault-fixing cannot start until your team is aware of the problem. The faster the alerts are delivered, the faster your team can get to the bottom of a fault and minimize losses. Adaptable integration suites can connect to enterprise systems to provide timely, automated alerts across all relevant teams. You can eliminate costly delays between fault-finding and fault-fixing and minimize downtime.

Impactful Collaboration

A data integration solution leverages intuitive visualization techniques to facilitate seamless collaboration between IT experts and non-technical staff, such as industrial engineers and supervisors. By drawing on the strengths of both groups, your business can optimize how it uses analytical fault-finding methodologies to investigate and resolve failures.

TIBCO Can Help You Improve MTTR With Unified, Real-time Data and Analytics

Effective fault detection goes beyond having the right technologies and skills for the job. All your resources must collaborate seamlessly to paint a complete picture of the problem and point toward a timely, effective resolution.

TIBCO offers manufacturing companies the technologies necessary to turn their factories into modernized, automated, and connected ecosystems. The TIBCO Connected Intelligence platform integrates data from all relevant processes, equipment, and Industrial Internet of Things (IIoT) devices to generate insights that inform successful FMEA and root-cause analysis. With TIBCO you can unify your data to gain a bird’s-eye view across your operations and identify any faults and weak points before they cause significant damage.

Want to see how unified data analytics can help you accelerate MTTR? Contact TIBCO today and request a demo.

The post Speed Mean Time to Repair with Analytics and Proactive Alerting first appeared on The TIBCO Blog.