什么是企业资产管理 (EAM)？

Enterprise Asset Management (EAM) is the systematic practice of tracking and monitoring the physical assets of complex organizations across large industries from acquisition through to disposal. Assets across all departments, locations, facilities are included, and can vary from buildings, plants, machinery, heavy and light equipment, vehicles, ships, planes, handheld devices, computers, and more.

Asset-intensive industries, like construction, energy, manufacturing, utilities, and government, struggle with tracking and measuring asset performance, reducing maintenance costs, and maximizing asset uptime. To account for and monitor such large numbers of assets, the adoption of Enterprise Asset Management software has become the standard industry practice for these large organizations.

Enterprise Asset Management software can be conceptually imagined as the organization's central inventory, with features for planning, funding, construction, maintenance, optimization, replacement, and asset disposal. These functions overlap computerized maintenance management systems (CMMS), however, modern EAM software further adds greater sophistication by employing Industrial IOT, automation and machine learning to efficiently monitor and analyze the state of assets well beyond the capabilities of CMMS software.

EAM features are vast, and perform many functions found in other packages, notably, the features of CMMS, and Application Performance Management (APM) software. Furthermore, EAM software integrates with ERP systems, and if necessary, with facilities management apps, fleet management software, and aviation maintenance, repair, and operations software.

Enterprise Asset Management software provides many features that are found in other software packages, however, EAMs are exceptionally robust, and designed to serve the complexity of multi-location, asset-intensive industries. To be considered an EAM, the package must include the following features.

• Asset Management — As a namesake, the asset management component manages the complex assets of the organization, providing features for: capital and expense projects, management of construction works, maintenance strategies, equipment costing and performance.
• Work Management — Supporting maintenance strategies, the work management component encompasses the following features: job planning and scheduling, executing maintenance and job completion, field service support, job and project cost analysis.
• Materials Management — Efficient inventory and materials tracking is essential for achieving business goals, this component includes project requirements determination, vendor management, inventory management, and contracts and procurement.
• Workforce Management — Like assets, workforces must be maintained, and if needed trained to learn new and evolving skills. The workforce asset management component includes features to achieve these goals, including job assignments and planning, time and attendance tracking, skills training management, health, safety, security & environment (HSSE) planning.
• Financial Management — System integrations allow EAM software to connect to accounting software to extend the EAM's financial components: project budgeting and forecasting, project costing, accounts receivable/accounts payable, continuing property ledger (CPR) of fixed assets.
• EAM Analytics — EAM analytics is the insight accelerator that enterprises use to stay competitive, these features should include asset and operation insights, informed decision making (predictive), improved outcomes (prognostics).

Large organizations with extensive assets, sometimes in the millions, are challenged with tracking, monitoring, managing, and optimizing the resources necessary to keep those assets operational, achieve business goals and maximize ROI. The solution is a purpose-built enterprise asset management system that is designed to support the largest most complex operational environments. Without such robust software, organizations would be at a loss, resorting to manual processes, or a hodge-podge of disparate software or technologies, disconnected and siloed, ultimately limiting overall effectiveness. With EAM software, compliance and best practices are built-in, maintenance teams can collaborate with managers more effectively, and organizations are empowered by:

• Centralized Asset Information — EAM systems centralize asset information so that maintenance managers can quickly see asset location, asset condition, maintenance schedules, and a roster of skilled technicians qualified to resolve issues.
• Consolidated Operational Workflows — In part due to the centralized asset information, EAMs also further consolidate processes, standardizing workflows across the entire organization and asset types making teams more efficient.
• Anticipate and Resolve Issues — Predicting critical events and determining preventative measures are major benefits in keeping equipment operational and reducing downtime. Further, this advantage positively impacts a company's ability to honor compliance demands.
• Smarter Asset Monitoring Maximizes Asset Use — Real-time monitoring coupled with AI techniques offers tremendous insight into the state of assets. With prognostic AI capabilities, scenarios can be built around a likely future outcome based on current conditions and usage, forewarning maintenance teams to accelerate future repairs. Such future forward maintenance helps to maximize asset utilization.
• Manage Asset and Infrastructure Life Cycles — Targeted preventative risk maintenance helps to extend asset life cycles and improve ROI.

Enterprise asset management integrates three key components, people, processes, and technology, to achieve effective performance that delivers value to customers. Consistent and reliable value delivery is ultimately the goal of EAM practices. The following EAM best practices highlights areas where focused organizational effort can bring positive impact.

• Choose The Right Technology — The market is saturated with vendors offering solutions with similar EAM features that may not be EAM software or are label EAM software but do not fit the complete definition of one. Understanding the difference between similarly functioning solutions can save a company money and frustration. EAM systems, APM systems, and CMMS systems, today, have many overlapping features, and though the main difference is the scale of business they serve (CMMS tend to be for small or medium businesses, and EAM for enterprise businesses), forgetting labels and aligning software features with company needs is a good start for choosing the right fitting package.
• Do Not Proceed Without an Asset Management Operating Model — An organization's asset management operating model is a complete framework of its business processes, organizational hierarchy, and data standards. Because EAM is a team effort, operating models map out the requirements and purpose of every process, role, and data set so every player knows what they are responsible for and how to achieve it. Asset management operating models are technology agnostic, and has been codified in the ISO 55000 and PAS 55 international standards
• Turn EAM Data into Informational Content — Data and data analysis has become the special sauce for high performing asset management operations. Data is unique in its ability to continuously provide deeper operational insights as more of it is captured, integrated and analyzed. Leveraging analytic technology, including AI and automation, and integrating disparate datasets together to find cross-departmental insights is complex, but has proven to yield game changing insights. For example, combining detailed equipment failure reports with costing information can pinpoint the recurring problems that are most costly and lead to better business decisions, inventory management, and asset utilization.
• Standardize EAM Across The Entire Organization — Geography, time zones, and the sheer number of team members involved in an organization's EAM presents serious management challenges. Like in any large organization, standards are the truest path towards organizational cohesion. Get all departments on the same page with an organization wide asset management operating model. Next, deploy centralized software and data systems which will help maintain standards, however, it should not be the source, using key performance indicators (KPIs) across all sites will standardize goals regardless of the tools teams use.
• Leverage and Institutionalize Maintenance Schedules — EAM is not just about maintenance, but maintenance schedules are an industry best practice. Knowing details like when, where, and for whom a particular job is for helps teams prioritize, coordinate, and communicate resources more efficiently. Creating purpose driven schedules, such as categorizing jobs into longer term "event schedules" (e.g., annual, semi-annual inspections), shorter revolving schedules (e.g., daily, weekly maintenance), or resource support schedules (e.g., equipment reservations), pays off big by efficiently allocating workers and resources.

The best EAM software systems keep pace with technological trends. Two trends impacting EAM designs are predictive and prognostic techniques enabled by AI, and Industry 4.0 automation technology.

Artificial Intelligence and predictive maintenance attempts to go beyond preventative maintenance or reactive maintenance models. using data analysis with asset characteristics, and other circumstantial data points, the system can optimally schedule maintenance events for workers. More advanced systems can collect greater sums of data and accurately prognose at what future time an asset is most likely to fail, and schedule repairs, order components, and allot appropriate workers.

Industry 4.0 technology includes IoT, automation, robots, smart factories, sensors, and cloud computing. The introduction of these systems has transformed asset intensive industries like manufacturing into globally expansive systems acting as one. EAM systems are challenged with these circumstances, as well as the advanced expertise required to administer them.