In the world of bottle neck competition, asset sensitive industries give the top priority to asset management. The major goal of the industries is to achieve the lowest life cycle cost and provide the best services or meet the production targets. Asset management is primarily based on collecting the asset information such as asset location, maintenance specific details, inventory, spare parts etc. But if the data is processed or acted upon, contributes in decision making. Analytics driven reliability and maintenance- Analytics driven reliability and maintenance is becoming the key element in the field of asset management. Asset analytics contributes for effective asset reliability & maintenance management and some of the benefits of effective asset management are listed below:
It facilitate greater control over asset by focusing on asset condition and work processes. It helps in limiting the unnecessary costs, and reduces cost of ownership and increases asset productivity. It improves maintenance efficiency and cost tracking.
In order to achieve effective asset management, the data generated from various EAM/CMMS is processed, analyzed and reports are generated. The reports are generated in the form or dashboards, maintenance scorecards, graphical representations etc. Asset Analytix provides data analysis and reporting solution for asset reliability and maintenance management. It guides the organizations to acquire information from EAM/CMMS systems efficiently and take the data driven decisions. Asset Analytix is specialized in providing the customized reports irrespective of reporting technology used.
There are also many different kinds of assets, with multiple types of processes that need to be taken into account, and any minor error in calculation or poor judgment will have serious consequences in the long run. Asset maintenance and management should not be left to the vagaries of a manual process, or subject to decisions made by individuals, no matter how experienced they may be. While the strength of the business may well be in its dynamism, asset monitoring solutions should be steadfast and predictable. Equipment maintenance has, for far too long, being mainly reactive and not proactive in the typical organization. While the piece of equipment in question may well have a great track record and be manufactured by a most trustworthy supplier, any number of factors can interrupt its productivity. Without a dedicated asset monitoring solution, unexpected failure can result in expensive downtime and a flurry of nonproductive activity.
Business chiefs hate unpredictability. Indeed, this is the greatest enemy. If productivity is less than 100% in real terms, the business starts to lose ground. A system of asset monitoring and alarming should help to reveal problems before they even exist in terms of real impact. Service providers can be summoned whenever predetermined triggers are exceeded. The beauty of real-time and comprehensive asset monitoring is that it provides benchmarks and traceable performance data. Imagine how this could enable the construction of a proactive maintenance plan based on a variety of different scenarios?
Forecasting failure risks. Mean residual life. Vendor performance OEE. Repair Vs replace.
These reports act as navigators and lead to: Increased asset availability and reliability. Reduced unplanned downtime. Identifies the underperforming assets. Reduces total cost of asset ownership. Extensive plant and equipment risk analysis. Predictive analysis. Considering entire life cycle of an asset, maintenance costs are major concern of any company's expense budget. Understanding this fact, companies are implementing strategies to revive the perception that "maintenance is an unavoidable evil to one, where maintenance acts as a vital contributor to the company's profitability". To leverage this, companies have integrated the computerized maintenance management system (CMMS) analyzing data generated from these systems is critical for decision makers. AssetAnalytix provides analytical reports that deliver data driven asset reliability and asset maintenance system management.
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