资产健康管理 (AHM)

Chinese chemical subsidiary of multinational corporation serves customers throughout the world. Sales offices and research and technology centers are strategically located to provide rapid response to customer requests. Just two workers were assigned to maintain thousands of intelligent instruments in three production units, so they could do little more than react to device issues as they appeared. This costly maintenance method inevitably led to unexpected downtime when a critical instrument failed. Plant management recognized the need to change from reactive to predictive maintenance for all assets, including instruments and control valves, but help was needed in implementing such a technology-based initiative.

A modern locomotive, for example, has as many as 200 sensors generating more than a billion data points per second. Vibration sensors surround critical components, video cameras scan the track and cab, while other sensors monitor RPM, power, temperature, the fuel mix, exhaust characteristics, and more.Most of today’s locomotives lack sufficient on-board processing power to make full use of all this data. To make matters worse, the data from different subsystems, such as the brakes, fuel system, and engine, remain separate, stored in isolated “boxes” that prevent unified analysis. The data is available, but the technology needed to process it in the most effective manner is not. As new sensors are added to the machine, the problem escalates.

The O&M division of an aerospace and global security company was using spreadsheets to manually track more than 3,000 assets assigned to students and staff. Maintaining audit trails for this high volume of equipment became increasingly time-consuming and challenging. The chore involved knowing precisely what equipment was on hand, what had been issued, its location and the name of the custodial owner of each item. Every aspect of this task was carried owner of each item. Every aspect of this task was carried out by individuals with spreadsheets. Manually documenting the full lifecycle of each asset added to the burden. This included tracking maintenance requirements and records, incidents and damages, repairs, calibrations, depreciation, and end-of-life data.