Asset Health Management (AHM)
Overview
Asset Health Management refers to the process of analyzing the health of an asset as determined by operational requirements. The health of an asset in itself relates to the asset's utility, its need to be replaced, and its need for maintenance. It can be broken down into three key components: 1) Monitoring: Tracking the current operating status of the asset. 2) Diagnostic Analysis: Comparing real-time data to historical data in order to detect anomalies. 3) Prognostic Analysis: Identifying and prioritizing specific actions to maximize the remaining useful life of the asset based on analysis of real-time and historical data.
Applicable Industries
- Automotive
- Transportation
Applicable Functions
- Discrete Manufacturing
- Maintenance
Market Size
From 2013 to 2022, the market for overall asset efficiency improvements potentially accumulates to USD 2.5 trillion.
Source: Cisco
Case Studies.
Case Study
Danish Cell Controller Project
Prior to 1990, most Danish electric power was produced at large, centralized generation plants from which it was transmitted and distributed to commercial, industrial, and residential consumers. Since then, thousands of distributed generators have been added such that the installed generation capacity at the distribution level exceeds the generation capacity at the transmission level. The distributed generation (DG) assets include dispersed combined heat and power (CHP) plants and wind turbines, creating a “carpet” of generation at the low and medium voltage levels of the distribution system (see inset). These distributed resources provide renewable and flexible energy production and support local thermal heating loads but were designed to operate only while grid-connected and could not be used in the case of a major power outage. The high penetration of variable wind generation also created the situation where the transmission system had to balance all the local variability of wind (both real and reactive power).
Case Study
Crossing the Atlantic to Argentina
Between 2005 and 2010, Aluar went through a substantial growth phase where most of the production facilities were upgraded. As a result of this expansion, the number of PLCs increased from 100 to 300. When it came to managing the control program software, however, flaws and cracks began to show in the established workflow and version control procedures that had prior to the growth phase, been based on manual backups and documentation. A rapid growth in the number of automation and maintenance staff (>100 users) also coincided with increasing accounts of infrequent and incomplete documentation of software versions, which then required an increasing effort where bug tracing and detection were concerned. This increased the risk of incidents that could not only affect operation, but that could also result in stoppages at the mid-term. It also increased the risk of safety risks remaining undetected.