Equipment availability rate, an essential component of OEE (Overall Equipment Effectiveness) or TEEP (Total Effective Equipment Performance), represents a fundamental indicator for any manufacturing company. With Quebec machines operating at only 35% of their potential availability on average, understanding and improving this indicator becomes crucial to maximize productivity without investing in new equipment. This article presents methods to effectively measure equipment availability rate and the tools at your disposal to transform this data into continuous improvement levers in the Quebec manufacturing context.
You may wonder what the difference is between OEE and TEEP? These two key performance indicators are often confused, but present important nuances.
OEE (Overall Equipment Effectiveness) is considered the first indicator to monitor in your factory. It's not the "holy grail" of indicators, but it sits at the highest level and integrates all factors affecting the performance of your equipment. It results from multiplying three sub-indicators:
TEEP (Total Effective Equipment Performance) mainly differs at the availability rate level. Unlike OEE, it takes planned stops into account in its calculation. It therefore uses the global utilization rate rather than the operational availability rate.
For example, for an 8-hour shift with 4 hours of effective operation:
You've probably already noticed that your equipment doesn't operate at full capacity. This is a reality shared by most industries. Equipment availability rate often represents the most problematic factor of OEE, with an average of about 35% in Quebec manufacturing companies.
This statistic reveals a considerable opportunity: before investing in new equipment, there is significant room for improvement on your current installations. The first step is to understand why your machines are not available when they should be.
The availability rate allows you to precisely identify the causes of unplanned stops. Are they frequent breakdowns, overly long tool changes, operator absences, or other factors? By isolating this indicator, you can target your improvement actions where they will have the most impact.
To effectively measure equipment availability rate, several approaches are possible depending on the nature of your machines and the resources available in your Quebec factory.
The most direct method for calculating availability rate is to track the actual operating state of the equipment. This isn't simply about knowing if the machine is powered on, but determining if it's actually in production.
To do this, you need to capture two essential types of information:
More importantly, you need to categorize the reasons for stoppages to identify the main causes of your equipment's non-availability.
For certain equipment, particularly those producing regular cycles, it's possible to deduce the availability rate from production cycle analysis:
This method has the advantage of being implementable without modifying existing equipment, which is particularly interesting for Quebec manufacturing industries with older machines.
You may wonder what concrete tools to implement to track this availability rate. Several solutions are available depending on the sophistication of your equipment and your resources.
Recent machines generally have communication protocols allowing direct retrieval of state data. These technologies offer several advantages for measuring availability rate:
Data is collected via protocols such as OPC UA, Modbus, or directly through equipment APIs, then interpreted to calculate machine availability rate.
Older machines, common in the Quebec industrial landscape, don't always have modern communication interfaces, but this doesn't mean they can't be monitored. Adapted solutions consist of:
These approaches allow conventional equipment to be transformed into connected machines capable of providing availability data.
For manual intervention workstations or equipment difficult to connect, assisted declaration systems can be effective for tracking availability rate:
These systems facilitate operator declarations while structuring data for analysis, particularly adapted to the realities of Quebec factories.
Measuring is only the first step. Intelligent exploitation of availability data is what truly allows performance improvement in Quebec manufacturing industries.
A relevant analysis of availability data helps identify and prioritize causes of stoppages according to:
This prioritization helps focus improvement efforts where they will generate the most impact on the overall availability rate.
One of the major advantages of equipment availability rate is that it can be measured and analyzed at different scales:
This multi-level approach helps identify bottlenecks and compare performance between different units.
Equipment availability rate constitutes a fundamental indicator for any Quebec manufacturing company. An essential component of OEE/TEEP, it offers a precise view of the effective use of your resources and often reveals significant improvement opportunities.
With an average equipment availability of about 35% in Quebec industries, the challenge is major: before investing in new machines, maximize the use of those you already own. To do this, precise and regular measurement of availability rate is essential.
To quickly improve the availability rate, start by identifying and eliminating frequent micro-stoppages, reduce tool changeover times by applying the SMED method, and implement intervention standards for common breakdowns. These actions can generate significant gains in Quebec factories without major investments.
If the Quebec average is about 35%, a good initial target would be to reach 60-65%. World-class companies aim for availability rates above 85%, but this progression should be made in stages according to the specific context of each industry.
Yes, the availability rate varies considerably according to sectors. Continuous process industries (chemical, food processing) tend to have higher rates than assembly or discrete manufacturing industries. These variations must be taken into account when establishing relevant benchmarks.
Costs vary enormously depending on the approach chosen. A structured manual solution can be implemented for a few thousand dollars, while a complete automated system can represent an investment of several tens of thousands of dollars for an average factory. The important thing is to start at the scale of a critical piece of equipment to demonstrate value before deploying more widely.
For an effective approach, analyze data daily at the operational level, weekly at the tactical level, and monthly at the strategic level. This multi-level approach allows rapid identification of problems while maintaining a long-term vision of availability rate improvement.
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