Analysis of world practices in the field of asset management

While Eastern Europe is still on track for modern approaches like Predictive Maintenance, Western countries have made significant headway in both strategies and implementation of Industry 4.0 concepts. The world’s best practices in asset management (such as Enterprise Asset Management or EAM systems) require you to go through the following stages:

• Collecting information about assets.
• Identification of the necessary tools for working with data.
• Customization, analytics and support of decision making tools.

One of the pioneers in the development of the asset management concept is the British Institute of Asset Management, which has more than 300 members around the world. The Institute develops standards and approaches in the field of asset management for manufacturing companies. In recent years, his efforts have focused on solving three key problems:

Reduced reactive maintenance costs

For many companies, a reactive approach to equipment maintenance seems to be the cheapest solution, especially when the unit is still in working order. But the trouble is – the cost of each accident with this approach increases significantly (ABS Group).

In addition, assets start to give out surprises like unplanned downtime and, as a result, reputation losses.

Modern equipment maintenance methods focus on a more productive solution. It collects asset data, analyzes equipment performance, and warns of possible downtime or accidents. According to McKinsey, this predictive approach saves about 25% of costs annually.

For example, the cleanup equipment for US oil giant OSRL should be in perfect condition in the event of a major oil spill. It is impossible to keep track of everything manually, so the company has implemented an EAM system and now sees the “health” of underwater and ground equipment in real time.

Unplanned downtime of critical equipment

Downtime continually undermines profitability and production efficiency. In the United States, every hour of unplanned downtime costs companies tens of thousands of dollars. The main reason is outdated equipment.

This happens when a company does not have a complete picture of asset maintenance and health. Without collecting, analyzing and interpreting asset data – from procurement to disposal – companies are reverting to reactive, that is, costly methods. Predictive approaches also solve this problem, thanks to which companies can save up to 10% profit on downtime (Plant Engineering).

US-based construction company LP Building has lost hundreds of thousands of dollars to unplanned downtime at 26 sites across the country. By implementing the EAM system and collecting all the data together, the oilmen were able to prevent downtime in time and save on repairs.

Poor inventory management

Inventory is the cornerstone of the efficiency and operability of all equipment, which without proper optimization becomes a blind spot and a black hole in the company’s budget. Businesses often plan and calculate inventory in Excel spreadsheets, making data unification and analysis even harder. As a result, situations arise when the repair of critical equipment is suddenly postponed due to the lack of the necessary components in the warehouse.

Fortunately, EAM systems make everything easier and faster. Within the system, any user can check the availability of necessary spare parts, automate the purchase of inventory and keep a clear record of supplies, payments, etc. According to Industry Today, saving on competent inventory is one of the main advantages of Industry 4.0 approaches.

In a word, with a unified system and clear analytics, companies extend equipment life, cut costs and fully control the purchase. Regardless of the structure and size of your enterprise, solutions like SmartEAM give you powerful tools to manage your critical assets.