「英中对照」Limble发布《维护状况报告》调查 称美国设施团队预防性维护完成率仅54%
Facilities teams often miss preventive maintenance, raising costs: Limble
Limble发布《维护状况报告》配套调查,覆盖686名美国维护与运营专业人士,结果显示受访团队仅完成54%的计划预防性维护。调查还显示,47%的维护负责人反馈典型月份非计划停机超10小时,漏做预防性维护或产生10万美元及以上停机成本;82%的受访组织使用CMMS但仅39%实现全员定期使用,超半数团队已使用或试点AI维护工具。
该调查披露了设施维护领域预防性维护落地、CMMS应用及AI工具导入的现实痛点,可为设施运营方优化维护体系、评估AI应用前置条件提供参考;其样本仅覆盖美国从业者,结论在其他区域的适用性需进一步核验。
An article from
Dive Brief
Teams complete just 54% of scheduled preventive maintenance, while 47% of maintenance leaders report more than 10 hours of unplanned downtime in a typical month, according to a new survey.
Published Oct. 9, 2026
First published on
Dive Brief:
- Missed scheduled preventive maintenance can lead to downtime costs of $100,000 or more, according to a Limble survey of 686 U.S. maintenance and operations professionals.
- In addition, 65% of survey respondents said that reactive, as opposed to preventive, maintenance increases risks to technicians.
- These findings can be attributed in part to “limited time for hands-on work, expertise that may never get documented, and inconsistent use of maintenance data as teams work to prevent failures and move beyond reactive maintenance,” Limble said in a news release.
Dive Insight:
The survey comes as manufacturers are increasingly turning to artificial intelligence and automation to improve various parts of their operations, including predictive maintenance.
According to the survey, more than half of maintenance teams said they were using or piloting AI tools to help them do their jobs, and 92% agreed that AI needs “good, complete maintenance data” to work properly. However, the survey found that few manufacturers actually follow a data management plan in its entirety, which can result in maintenance issues that could have been prevented.
“Most maintenance teams aren't short on technology. They're short on time and information they can trust," Limble CEO Gary Specter said in a statement. "Adding AI won't automatically solve the problems they face every day. We have to make it easier for the technician to capture what they know and give teams information they can use to act before a failure happens.”
“Teams have to fix how maintenance work gets recorded before AI can do much with it,” Limble said in its State of Maintenance Report, of which the survey was a part. “AI in maintenance runs on the records a team already keeps, making the quality of those records the thing that decides how far it gets.”
Other key survey findings include:
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Although 82% of survey respondents said their organization uses a computerized maintenance management system, only 39% said their entire team uses it regularly, and 71% reported that someone on their team asked for information that their CMMS already contained.
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Sixty one percent of respondents said the way they currently approach maintenance increases the risk of unplanned downtime, higher costs and safety issues. Unplanned work is often done under increased time pressure and on equipment that is too hot to handle safely, Limble said.
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Nearly three quarters said they rely on a “critical facility asset” that only one team member knows how to repair, while 47% said they have lost irreplaceable maintenance knowledge due to staff turnover.
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Forty eight percent of respondents said they use preventive rather than predictive maintenance, although the survey’s “work score” pegged that figure at 68%.
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Staffing shortages were cited as the single biggest obstacle to better maintenance practices, followed by aging equipment, budget constraints and “too much reactive work.”
来源:Facilities Dive 设施运营新闻 · facilitiesdive.com