Predictive Maintenance

Predictive maintenance is a strategic approach wherein the ongoing status of equipment is systematically observed and analyzed to anticipate potential equipment failures before they manifest. The primary goal of is to optimize the scheduling of maintenance activities and minimize the downtime of equipment.

By leveraging the data obtained through continuous monitoring, assesses the likelihood and severity of performance degradation or failure. This enables maintenance tasks to be executed with greater precision and cost-effectiveness, driven by real-time evaluations of equipment conditions.

The prerequisites for a successful predictive maintenance program may vary depending on the organization and the specific equipment in use. However, meticulous planning and research to establish baseline conditions for the equipment always play a pivotal role in the effectiveness of any initiative.

Advantages of Predictive Maintenance

Cost Reduction:

• Decreases ongoing maintenance costs significantly.

• Customizes maintenance based on current conditions, reducing redundancy.

• Cuts maintenance costs by 50% or more by eliminating pre-defined schedules.

Failure Prevention:

• Reduces the frequency of unexpected or catastrophic equipment failures.

• Detects signals of degradation in worn or defective components.

• Establishes a proactive response loop, leading to longer equipment life.

Inventory Optimization:

• Streamlines spare parts inventories by sourcing parts on an “as-needed” basis.

• Creates a lead time buffer for part replacement through predictive feedback.

• Reduces the need for extensive stockpiles for both scheduled and unscheduled maintenance.

Operational Efficiency:

• Utilizes historical data and analytical capabilities for more visibility into equipment performance.

• Enables accurate predictions of service life and mean time between failures.

• Facilitates systematic capital expenditure planning.

Safety and Morale Improvement:

• Enhances operator safety by avoiding potentially dangerous catastrophic failures.

• Improves overall operational efficiency, contributing to increased morale.

Condition-Based Maintenance vs Predictive Maintenance

Condition-based maintenance revolves around monitoring physical symptoms linked to equipment and component degradation to predict and address impending failures. It often employs the P-F interval, the duration between the first signs of degradation and the actual failure, to proactively plan part replacements or repairs before failure occurs. The efficacy of condition-based maintenance heavily relies on the consistency of these P-F intervals.

While the term “condition-based maintenance” is sometimes used interchangeably with “predictive maintenance,” it’s crucial to recognize that the former is just a pivotal component of the latter. It  goes beyond relying solely on condition-based data; it integrates historical trends, risk factors, and additional process sensor data to form an intelligent and adaptive approach that drives the overall maintenance operation.

In essence, elevates the strategy by analyzing signals and trends, transforming them into actionable insights and alerts. This approach adds a layer of intelligence and prioritization, surpassing the more singular focus of condition-based maintenance.

Preventive Maintenance vs Predictive Maintenance

Preventive maintenance, also referred to as planned maintenance, is based on pre-established time or usage intervals to determine servicing, parts replacement, or the calibration of equipment. While the frequency of preventive maintenance intervals can be adjusted based on historical trending, risk tolerance, and other factors, the maintenance tasks performed with each repetition will generally remain unchanged.

Preventive Maintenance:

Foundation:

• Based on pre-established time or usage intervals.
• Determines servicing, parts replacement, or equipment calibration in advance.

Flexibility:

• Frequency of maintenance intervals can be adjusted based on historical trends, risk tolerance, and other factors.
• Maintenance tasks remain generally unchanged with each repetition.

Efficiency:

• Generally less expensive to implement initially.
• Can be costlier to maintain on an ongoing basis due to fixed schedules.

Approach:

• Takes a proactive approach to avoid potential failures and extend equipment life.

Predictive Maintenance:

Foundation:

• Essentially a form of preventive maintenance with a significant distinction.

Adaptability:

• Provides adaptive maintenance intervals and service requirements based on real-time equipment assessments.

Efficiency:

• Enables more efficient maintenance through real-time assessments.
• Averts premature replacement of viable parts.

Cost Comparison:

• Typically incurs higher ongoing costs compared to preventive maintenance.
• Studies show savings of approximately 8% to 12% over preventive maintenance and up to 40% over reactive maintenance.

Intelligence:

• Adds a layer of intelligence and prioritization to the maintenance strategy.
• Analyzes signals and trends, transforming them into actionable insights and alerts.

Predictive Maintenance Software

Enhancing equipment management relies on advanced software to gather, analyze, and store crucial data for each piece of equipment, and at its core is the Computerized Maintenance Management System (CMMS).

CMMS as the Engine:

• Employs algorithms to proactively identify trends.
• Automatically generates alerts and work orders for timely maintenance responses.

Comprehensive Features:

• Serves as a centralized platform for maintenance history, work order management, parts inventory control, asset management, and report generation.

Value Addition:

Long-Term Perspective:

• In industries where equipment life spans decades, CMMS ensures recording and maintenance of asset history.
• This data becomes a valuable resource available for review on demand or integration into predictive maintenance algorithms.

Wireless Technology Integration:

Mobile Solutions:

• Top CMMS software utilizes the latest wireless technology.
• Mobile CMMS solutions enable continuous tracking and response to critical maintenance issues from anywhere.

This maintenance software is powered by CMMS, not only facilitates real-time equipment assessments but also enhances overall efficiency by providing a comprehensive platform for managing maintenance operations.

Predictive Maintenance ROI

Start-up costs for this program encompass software, sensing equipment, training, installation, and other implementation expenses. While these initial costs may surpass those of conventional preventive maintenance systems, the potential savings make the return on investment (ROI) substantial.

Beyond Cost Reduction:

• The program not only reduces maintenance costs but also cuts equipment downtime by 40% or more.
• Productivity gains of up to 25% contribute significantly to overall ROI.

Quick Recoup:

• The combination of reduced costs and increased productivity enables a swift recoup of initial investment.
• Across various industries, an average ROI of 10x is achievable.

Staged Implementation:

• To minimize upfront costs, a staged implementation strategy is viable.
• Early focus on expensive, heavily utilized, or failure-prone equipment allows adapting to new processes gradually.

Adaptable Strategy:

• Predictive maintenance, addressing ongoing costs and preventing disruptive downtime, promises a substantial return in a relatively short period.
• The staged approach facilitates organizational adaptation to new processes and technologies.