Plan maintenance for legacy machine tools

Be smart, be connected

Computerized machine maintenance system

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Industry 4.0 technologies and the Industrial Internet of Things (IIoT) have transformed the machine shop environment, providing new business opportunities and improving competitiveness. Yet many small and medium-sized enterprises (SME), having invested in modern equipment, struggle to integrate the maintenance of their legacy machines into the new digital and smart manufacturing paradigm.

Smaller businesses may have only legacy machines, seeing digitalization as unachievable because of the required costs and skills. It's worthy of note that while the term legacy suggests outdated and old-fashioned, it actually refers to machines that are unable to support real-time communication with third-party software.

Most legacy machines are central to business success, having absorbed considerable investment and built in-house operational and maintenance knowledge. Maintenance spares inventories are comprehensive, and spares costs are reasonable. Fully depreciated, such equipment adequately meets manufacturing needs and will do so for many years. Yet many SMEs find themselves squeezed between prohibitive capital expenditure requirements to retool with modern equipment and the risk of falling competitively and technologically behind.

Think Smart, Think Modular

In recognition of this issue, modular aftermarket systems have become available, allowing connectivity retrofits for non-IIoT equipment. At their most basic, they comprise sensors and Wi-Fi-capable communication devices that use standard data-transfer protocols or protocol converters. Business owners now have a low-cost path to integrate legacy machines with third-party maintenance management systems through targeted equipment upgrades.

Retrofitting legacy equipment with connected sensors provides a step change in asset management opportunities for maintenance and engineering staff. Maintenance strategies for older, unconnected machines predominantly involve preventive maintenance. Cheap to implement and simple to operate, such a system is effective, but it has hidden costs. Preventive maintenance strategies tend to over- or undermaintain equipment, disrupt production, and require holding higher spares inventory.

No Replacement for Experience

A condition-based maintenance strategy can be used where sensors are fitted to monitor vibration, temperature, and even sound. While an improvement over preventive maintenance, such strategies require data collection and manual analysis before maintenance actions may be planned and implemented. Condition-based maintenance depends on expert judgment to operate; it occurs in hindsight and heavily depends on correctly identifying failure modes and tracking the correct data.

Integrating legacy machines with existing IIoT networks and modern computerized maintenance management systems (CMMSs) offers the opportunity for an evolutionary step change in maintenance strategies.

Predictive maintenance is the 21st-century evolution of condition-based maintenance, using predictive algorithms and machine learning to analyze data in real time. Foretelling failures and optimizing maintenance, predictive maintenance software can schedule downtime to minimize disruption by allocating maintenance tasks. Spares inventory is optimized, maintenance resources scheduled and minimized, and equipment uptime maximized.

Beyond PM

Beyond predictive maintenance lies prescriptive maintenance, with such systems offering both operating and maintenance options to manage equipment uptime and mitigate against identified future failure.

There is a cost of retrofitting legacy machines, both in dollars and disruption. There also is a risk of opening potential vulnerabilities into existing IIoT and CMMSs through retrofit. Further concerns lie ahead for SMEs that attempt an in-house resolution to address their immediate connectivity problem, risking a similar legacy discussion in a few years as software and technologies change and scale.

So, while integration drawbacks exist, an automated retrofit's modular nature provides flexibility and control through staged upgrades. Starting small, SMEs can identify and address roadblocks and problems at a small scale before intensifying the upgrade.

Connectivity vendors can map a staged rollout at a cost and timetable to suit the client. They also can better anticipate market direction and offer devices that can scale and adapt to business and technology changes.

A recent McKinsey report estimates IIoT applications will benefit global factories by $1.2 trillion to $3.7 trillion. Half of this benefit is estimated to be from operations optimization, tracking, monitoring, and adjusting machinery using sensor data. The next most valuable contribution is through the use of predictive maintenance and inventory optimization.

A complete rip-and-replace strategy of legacy equipment is financially impossible for most businesses, and the ready availability of external legacy connectivity technology makes it unnecessary.

With a planned and staged implementation starting on less-critical equipment, machine shops can iron out initial integration issues while learning which data to monitor and how best to use it. External providers can provide a roadmap to full integration, meeting both financial and strategic constraints. The use of expert external suppliers ensures the suggested options are fit for purpose, scalable, and futureproof.

Digitalization promises improved insight into operations to support informed decision-making for process improvements. In conjunction with a modern CMMS, it allows access to advanced maintenance strategies using artificial intelligence, machine learning, and predictive algorithms.

Industry 4.0 connectivity is now available to all, offering a short ROI, improved OEE, optimized asset longevity, reduced maintenance costs, and smaller inventory holdings.

Bryan Christiansen is the founder/CEO of Limble CMMS, 3290 W. Mayflower Ave., Lehi, Utah 84043, 801-851-1218, www.limblecmms.com.