MRO Spare Parts Optimization – IBM Blog
Many managers in asset-intensive industries such as energy, utilities, or process manufacturing perform a delicate and critical task when managing inventory. Finding the right balance is important to ensure the success of your maintenance, repair, and operations (MRO) initiatives, especially the spare parts that support them.
What’s at stake?
Whether your MRO process addresses preventive maintenance, service disruptions, or downtime overhauls, the desired outcome is the same. This means providing improved service levels, functioning safely and sustainably, operating efficiently, and reducing unplanned and costly downtime.
A recent report found that the cost of manufacturing downtime will increase significantly from 2021 to 2022. Fortune Global 500 companies are currently losing 11% of their annual revenue, up from $864 billion to nearly $1.5 trillion from 2019 to 2020. One
Another study found that:
swinging pendulum
MRO spare parts inventory varies by industry and equipment, ranging from specific items to including more basic consumables. These supplies include everything from large infrastructure items such as turbines, generators, transformers, heating, ventilation and air conditioning systems to smaller items such as gears, grease and mops. Many asset-intensive businesses are prioritizing inventory optimization due to increasing Industry 4.0 compliance, ongoing digital transformation, and cost reduction needs.
Over time, inventory managers have tested different approaches to determine which method works best for their organization.
Preferred by companies for many years at the right time operate This is the most logical approach to managing inventory and minimizing carrying costs. But recent disruptions to global supply chains due to the pandemic and regional challenges have caught many off guard.
When operations required spare parts that were not readily available, this often resulted in equipment downtime or costly inventory shortages. In the past, using this method often resulted in additional costs for expedited delivery or delivery along with concerns about part quality.
When you consider that IDC surveyed 37% of companies that use spreadsheets, email, shared folders, or an uncertain approach to manage their spare parts inventory, it becomes clear that this practice carries more risk than you might think.2 If demand forecasts are inaccurate, adopting a reactive approach may be less effective.
Now consider the following: just in case draw close. Some managers choose to stockpile extra spare parts due to past delays and other negative consequences. Maintaining safety stock is beneficial, but excess inventory costs money and takes a significant amount of time to manage. If your assets lack importance and priority assignment, you run the risk of accumulating unnecessary parts that could end up becoming useless on the shelf. This, in turn, begins a cycle of ongoing spending on inventory reduction efforts.
The Benefits of Finding the Right Balance
So when considering the downsides of both just-in-time and just-in-time approaches, the goal is to find the ideal balance that helps you get the right materials to keep your business running, while also giving your team what they need. appropriate time.
This is not purely theoretical. Balancing the dynamics of MRO spares and material demand offers quantifiable benefits. Many organizations lack the internal resources or knowledge to implement these required procedures, but those that are able to do so report:three
- all 50% Reduce unplanned downtime related to parts.
- all 40% Reduce inventory costs.
- all 35% Reduced maintenance budget.
- all 25% Service levels improve.
How to strike the right balance
The short answer is to collect, analyze, and act on data in real time to create immediate value across your operations. Easier said than done? Maybe you only rely on spreadsheets, physical asset counts, or condition monitoring.
Consider the following questions:
- Is there a platform that combines statistical analysis, prescriptive analysis, and optimization algorithms?
- Is it possible to segment data from all systems such as enterprise asset management, enterprise resource planning (ERP), customer relationship management and sensor technology using key parameters such as cost, criticality, usage, actual lead time, etc.?
- If you rely on a transactional ERP system, are you lacking the critical analytics and reporting capabilities your asset-intensive industry needs and are you aware of the gap in SAP?
- Can I review historical data modules?
- Do you perform a baseline analysis looking at inventory value based on average prices, inherited items, and other criteria?
- Can you do a what-if scenario to visualize your options?
- Are there any algorithms specifically built to improve intermittent and variable demand forecasting?
- Can you use work queues to group and prioritize tasks and monitor progress by organizational area and data set?
Artificial intelligence (AI) is already influencing the plans of many inventory managers, but it’s worth keeping an eye on the latest iterations of the technology. Generative AI has the potential to provide powerful support in key data areas.
- Master data cleaning to reduce duplication and flag outliers.
- Master data enrichment to enhance classification and material properties.
- Master data quality to improve data scoring, prioritization, and automated validation.
Explore optimization
IBM® MRO Inventory Optimization helps you optimize MRO inventory by providing an accurate, detailed picture of performance. The flexible and scalable solution is a fully managed cloud inventory platform designed to collect, store, and analyze massive amounts of MRO inventory inventory data by intelligently optimizing MRO inventory using a variety of advanced algorithms and analytics.
IBM supply chain consulting services also strengthen supply chain management, helping clients build resilient, agile and sustainable end-to-end supply chains for the future.
Supply chain innovation
- Siemens, the real cost of downtime in 2022
- June 2022, IDC SaaS Pathway Survey, #US49286022
- Based on IBM internal analysis of customer data. Results may vary.
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