Asset Management Software
Asset management software provides tools and interfaces for tracking and optimizing assets. Assets may include inventory, physical equipment and personnel. Decisions about purchases, liquidations, replacement and servicing are tracked with asset management software. In addition, asset acquisition and servicing budgets are estimated and tracked with asset management software.
Asset management software is used to track and schedule asset maintenance, which helps plant operators intelligently reduce downtime. Asset management software provides a top-down view of an organization’s assets, allowing operators to orchestrate the entire manufacturing process.
The most basic asset management software is specialized spreadsheet software that requires extensive human interaction in order to be effective. Manual data entry of asset information, both at acquisition and during the lifetime of the asset, makes basic asset management software labor-intensive and sensitive to errors made during human input.
More advanced asset management software may include manufacturer-provided asset information, including guidance on how often to schedule asset maintenance.
The most advanced asset management software uses machine learning to detect and predict asset maintenance requirements. Predictive maintenance is quickly becoming the standard used to reduce downtime in a variety of industries.
Asset management software relies on high-quality data for its effectiveness. Many asset management software programs now provide the option of direct integration of equipment sensor data, allowing a plant operator to quickly assess the condition of a facility as a whole. Plant operators can access previously siloed information to make better decisions about asset use and plant performance.
Asset management software can be hosted locally at a facility, centrally at a company’s headquarters, and in the cloud, with software as service implementations. Increased sensorization and the Industrial Internet of Things (IIoT) provide greater flexibility about where asset management software can run. IIoT allows companies to connect asset information to the cloud, which means information about an asset can be accessed from any device with an Internet connection. Wireless networking of these sensors removes the cost of physically connecting an asset’s sensors to a network.
Many asset management software solutions can leverage the ubiquity of smartphones. Work orders for asset maintenance, as well as images of assets or equipment, can be instantaneously introduced into the asset management system. Uploading information through either specialized phone apps or web portals improves an organization’s response time, while also reducing the paperwork required for day-to-day operations.
Advanced asset management software suites can provide recommendations about asset maintenance and when to schedule planned downtime. Machine learning algorithms can alert plant operators when assets exhibit signs that precede equipment failures.
Asset management software is limited by the amount of information available to it. Historically, staff manually entered information typing in work and service reports by hand. The task of drawing conclusions about plant maintenance and manufacturing downtime would fall to the personnel using the software.
Cheap sensors and reliable wireless networking have automated the process of loading plant data into asset management software. Prior to these developments, it was much more expensive to present real-time information about an asset, meaning fewer pieces of data about an asset’s current state would be available to the software.
The flood of data has presented a challenge for human operators. This challenge has been met by artificial intelligence (AI). Machine learning algorithms can make sense of the enormous datasets being created and properly trained software agents can make informed asset maintenance recommendations.
An asset management system needs defined goals. Whether the goal is to maximize the lifetime of the assets being managed, reduce downtime, or maximize short-term production output, a well-articulated guiding principle will inform how an asset management system is deployed.
An asset management system requires an accurate accounting of the assets to be managed. This should be as specific as possible, ideally including information such as the acquisition of the assets, usage location, past and current usage and service histories. In short, anything that happens with and to an asset should be recorded. This can be labor-intensive when performed by an employee, but IIoT’s ability to aggregate large amounts of data from sensors allows companies to capture much more complete asset histories.
Finally, an asset management system requires asset management software to synthesize the goals of the enterprise and information about the managed assets to guide decisions about operations.
What is the best asset management software?
The best asset management software incorporates machine learning algorithms to leverage real-time sensor data as well as historical data. The best software allows for IIoT integration to reduce labor costs associated with data input.
How does asset management software work?
Asset management software provides tools to track and monitor assets through the lifetime of the asset. At the bare minimum, asset management software provides a central system for recording the acquisition and maintenance history of assets. More recent implementations of asset management software leverage the widespread adoption of smartphones and tablets to both monitor and control assets on site. Asset management software can directly integrate real-time sensor data for use with a predictive maintenance tool.
What is asset tracking software?
Asset tracking software is a subset of asset management software that focuses on the locations and service histories of assets. Asset tracking software includes geospatial mapping abilities, which may not be present in all asset management software.