Spare parts management involves balancing the timely availability of spares and minimizing capital blocked in overall inventory. Poor spare parts management directly leads to poor asset availability and plant reliability. Organizations, faced with the complexity of spare parts optimization, must have better control over MRO inventory.
Comprehensive data analysis develops greater understanding and visibility of all aspects of spare parts management. The insight obtained by in-depth data analysis can help organizations build and execute better strategies.
Challenges in spare parts management:
- Ensuring timely spares availability to ensure greater asset availability
- Getting timely alerts on stock-outs of critical spares
- Identifying exceptions, outliers and issues for better inventory control
- Monitoring inventory turns, spillage and carrying costs
- Understanding blocked capital and inventory carrying cost
- Making informed financial planning and budgeting decisions
- Optimizing overall MRO inventory
How data analysis helps in spare parts optimization?
- Identification and management of slow moving, non moving and obsolete items
- Understand physical placement options for items to increase store room efficiency
- Monitoring of spare part availability for upcoming PM’s
- Understand consumption patterns and capital investment by performing ABC Analysis
- Critically rank and categorize items based on various procurement constraints and options
- Manage inspections, cycle counts and expiry
- Set min, max levels
- Determine economic order quantity (EOQ)
- Define stocking policies for capital and rotating assets or subassemblies
- Provide supporting analysis for building comprehensive strategies, executing strategic action plans and monitoring outcomes for timely adjustments
- Optimize inventory by balancing financial and reliability variables
- Increase productivity
- Reduce compliance risks
- Lower maintenance cost
- Gain visibility across the enterprise with well defined performance metrics
- Reduce unplanned downtime, increase reliability of critical equipments
- Spare parts optimization
- Determine root causes of non-conformities
- Increased ROA
- Reusable DW data models, ETL, metrics, scorecards, reports, KPI’s and OLAP
- Bridge gap between end user's perceived needs and actual business requirements
- Awareness of data analysis capabilities
- Improved data quality
- Ability to integrate other data sources outside of EAM for more comprehensive reporting
- Better leveraging of transaction data and IT infrastructure
- Time to focus on other projects
Our methodology and analysis techniques
- Determine Stock out Risk/Probability for critical assets spares using Weibull analysis
- Identify bottlenecks in the spares supply chain process by applying six-sigma analysis.
- Understand procurement efficiency by tracking KPIs for each PR
- Optimize stock holding with FSN and ABC Analysis.
- Forecast erratic spares demand by using Croston/ARIMA method.
- Identify slow moving and non moving items.
- Determine spare parts cost for budgeting purposes based on the Croston's Method.
- Find optimum spare parts inventory level.
- Understand demand patterns by classification based on Smooth. Irregular, Slow-moving. Mildly Erratic, Highly Erratic etc