Maintaining Your Maintenance Edge

November 13, 2023

Understanding essential differences among preventive, predictive, and prescriptive approaches for boxmakers

Corrugated paper and board packaging is steadily growing due to the global expansion of the e-commerce market, which heavily relies on corrugated products for shipping and the demand for sustainable packaging by replacing plastic with paper-based products. An increasing number of businesses are choosing to invest in corrugated packaging as their main packaging material because it can be created easily, is recyclable, and lowers overall shipment costs. As this presents opportunities, corrugated board manufacturers must keep pace and have been looking to software and technology to help them optimize their production processes and maintenance operations.

To accommodate the growing adoption of corrugated board by many industries, manufacturers are looking to scale their production in smarter and more efficient ways—while maintaining a competitive edge. According to SkyQuest Global Corrugated Board Market Insights, the global corrugated board market is projected to grow from $134.7 billion in 2022 to $238.1 billion by 2030.

Both corrugated board and box manufacturers are investing in digital transformation driven by Internet of Things (IoT) technology advancements. They have become acutely aware that by replacing traditional (often paper-based) methods with these advanced technologies, downtime is lessened, operations are more streamlined, and lost productivity is mitigated. Operational disruptions can cause maintenance staff to divert time from scheduled projects and can have significant negative business implications, including lost revenue, unplanned expenses, missed deadlines, and damage to a company’s reputation.

Because corrugated industry companies rely on a variety of specialized equipment and machinery to operate at peak efficiency and performance levels, they require up-to-date maintenance strategies capable of reducing rates of unexpected breakdowns. Traditionally, maintenance strategies were either preventive or reactive, by which equipment is maintained on a set schedule or repaired when it fails. However, these strategies are radically changing due to technological advancements in data analytics, artificial intelligence, and machine learning.

Preventive, predictive, and prescriptive approaches are all valid ways to streamline plant equipment management and are a major step up from the “don’t fix it until it breaks” approach. This article will explore the differences among these three ways to maintain plant equipment efficiencies and look specifically at the opportunities offered by computerized maintenance management systems (CMMS) software.

Preventive Maintenance—Covering the Bases

The main goal behind preventive maintenance (PM) is for the equipment to perform from one planned service to the next without any failures. Regular maintenance, when properly matched with a company’s unique maintenance needs in terms of equipment type, criticality, and scale, can help a company avoid expensive repairs, costly replacements, and operational downtime. For all of the intricacies of corrugated board and box manufacturing, maintenance planning can help ensure the required parts are in-house and appropriate staff time is allocated.

There are seven main steps to consider when implementing a new PM program or improving a current one. First, carefully consider the company’s maintenance needs, develop a comprehensive outline that defines all equipment and maintenance tasks, and set maintenance schedules. From setting program benchmarks, goals, and key performance indicators (KPIs) to leveraging the right supportive technology and training, each foundational step of preventive maintenance ensures the overall program’s success.

A company must first determine the project’s scope and requirements. These considerations are based on the number of machines or equipment that need to be maintained as well as their age, usage, operating environment, risk to operations, and manufacturer’s recommendations. A program outline can then be created that details the maintenance procedures, maintenance schedules, and required staff.

For example, boxmakers using a PM strategy often make use of manufacturer data on a part’s repairs and breakdowns to schedule maintenance before failure occurs. For instance, if a drying machine blower typically fails in four years, the maintenance team may opt to replace it in three years and 11 months, eliminating the potential for unscheduled downtime.

Supported by CMMS software, the maintenance program can be tracked and measured over time to determine its success and identify areas for continuous improvement. The CMMS solution should be 100% HTML5-compliant, mobile-friendly, and easily adaptable for user acceptance, and it should provide a complete overview of the company’s assets, including maintenance history, warranty details, and current equipment status.

The limitation of this preventive approach is that it relies on the law of averages. Assuming all assets of the same type are created equal—and that’s not usually the case—you may be replacing a part that might actually have a lot of life left in it. For example, if specific parts such as roller bearings are at the end of their normal life cycle, replacement is recommended. Alternatively, if a specific part happens to be toward the short-lived end of the normal distribution, it could fail if you waited to replace it based on its average life span.

Predictive Maintenance—A Better Approach

Also strongly supported by CMMS software, predictive maintenance (PdM) is a proactive maintenance approach known for its ability to optimize maintenance and asset management operations, reduce downtime, improve machine performance, reduce costs, and enable data-driven decision-making. It determines the condition of in-service equipment in order to estimate when maintenance should be performed. This approach promises cost-savings over routine maintenance or PM because tasks are performed only when needed.

Before reaping the benefits, you must successfully integrate PdM into your facility’s process structure, which will require an upfront investment in equipment, software, personnel training, and stakeholder buy-in. Nevertheless, PdM will deliver a well-planned implementation project combined with ongoing training, monitoring, and management.

It’s best to find a CMMS software that integrates with control systems and IoT-enabled assets to monitor each machine’s specific state in real time. Such information can be used to avert problems—for example, based on past experiences, if a particular brand of motor is likely to fail within a day and then it is noticed that it has started running hotter than normal. This is knowledge worth being armed with because staff could immediately repair or replace the item anytime that brand of motor’s temperature spikes.

To maximize the benefits of a PdM program, it’s crucial to take proactive steps such as setting alarms and alert thresholds, regularly reviewing collected data, and training staff to interpret that data. By doing so, you can identify potential problems early and take corrective action before equipment fails.

A checklist (see example below) can help ensure all necessary steps are taken to establish and maintain a successful PdM program, from sensor installation to data collection and analysis to maintenance planning and scheduling.

Along with the hardware and software checklists, a fully trained maintenance team will be required to support the PdM strategy and to ensure you the best return on investment on the maintenance strategy.

It will also be necessary to monitor KPIs such as mean time between failure, mean time to repair, and overall equipment effectiveness. Tracking performance KPIs is essential to enable the maintenance team to improve the efficacy of your program.

Prescriptive Maintenance—A More Comprehensive Approach

Prescriptive maintenance (RxM) is an advanced maintenance strategy that uses machine-level sensors and other monitoring strategies to determine when complex equipment and machinery require maintenance. It is a type of condition-based maintenance supported by CMMS software that uses real-time data from equipment, advanced analytics, and machine-learning algorithms to predict when maintenance is required and recommend the most appropriate and effective maintenance actions.

Its data analytics processes are used to calculate the equipment’s remaining useful life, enabling operators to perform maintenance before faults occur, similar to the philosophy of PM. However, unlike PM, this approach doesn’t rely on a predetermined schedule or cycle. Instead, it aims to identify the optimal moment to perform maintenance, whether by postponing or anticipating it, thus minimizing downtime.

RxM is generally best suited for enterprise companies that have to maintain equipment with complex failure modes with high levels of criticality and where high costs or safety implications are associated with equipment failure. It’s also a recommended choice for difficult-to-access equipment on which maintenance is costly and difficult to perform.

Both PdM and RxM strategies are effective and advanced, and they rely on sophisticated CMMS solutions. While both strategies use similar technologies, it’s helpful to understand the differences between the two.

The comparison below illustrates differences, goals, the data these approaches use, and the maintenance actions recommended. Understanding these differences can help organizations determine which approach is best suited for equipment and maintenance needs.

Embrace the Advances

For the corrugated board and box manufacturing industries, which rely on a variety of specialized equipment to maintain process improvement, successful maintenance strategies are key to operating at optimum performance levels that will ensure a competitive advantage.

Whether choosing either a preventive, predictive, or prescriptive approach, the successful manufacturer will embrace the advances made in technology that are embedded in CMMS software solutions to support their maintenance strategies. Companies should do everything possible to ensure their assets are dependable, perform at peak levels, and operate with the least maintenance and downtime.