1  2	All Asset Life Cycle Calculator Failure Analysis Inventory Life Cycle Cost Planning PM & PdM Reliability Resources Mgmt.

1	Breakdown Analysis Breakdown Analysis (RH_SM_FAL_004_0010) The report monitors and projects the downtime summary of the equipment. This is a drill-down report which further allows to drill it to the details and root causes to identify / analyze the failures.
2	Economic Order Quantity Economic Order Quantity (RH_CAL_001) Economic Order Quantity (EOQ) Calculator find the optimal quantity to order that minimizes total variable cost required to order and hold inventory.
3	Failure Data Analysis & Competing Risks Failure Data Analysis & Competing Risks (RH_SM_FAL_001_0007) This model will identify the failure causes which affects the reliability of an asset.It will also show the significant difference in reliability of an asset after removing failure cause(s).
4	Fishbone Diagram for Cause & Effect Fishbone Diagram for Cause & Effect (RH_SM_FAL_001_0021) Helps to determine root causes.Encourages Group participation.Increases process knowledge.Indicates possible causes of variation.
5	Forecasting Erratic Demand of Consumable Spare Parts using Croston Forecasting Erratic Demand of Consumable Spare Parts using Croston (RH_SM_SPR_001_0018) Croston's Method is used to forecast the demand for consumable spare parts in advance.It will help in planning and budget for inventory.
6	Forecasting Failures using Crow AMSAA Model Forecasting Failures using Crow AMSAA Model (RH_SM_FAL_003_0009) Crow AMSAA model will be used to find MTBF and confidence interval for MTBF. It will also find the trend and estimate number of failures for an asset.
7	Forecasting Number of Failures using Time Series Forecasting Number of Failures using Time Series (RH_SM_FAL_007_0013) Number of Failures for class of asset or an asset will be foretasted using Time Series Model.
8	Forecasting Spares Demand using Expo Method and ARIMA Forecasting Spares Demand using Expo Method and ARIMA (RH_SM_SPR_003_0020) Using Advanced Time series Technique ARIMA spare parts demand is foretasted.
9	Forecasting Time Between Failures using Expo Smoothing Forecasting Time Between Failures using Expo Smoothing (RH_SM_FAL_006_0012) Time Between Failures for an asset will be forecasted using Time series model.It will help to estimate next few failures for an asset.
10	Forecasting Total Maintenance Cost Using Exponential Smoothing Forecasting Total Maintenance Cost Using Exponential Smoothing (LCC_016) Total maintenance Cost for a site ,Location,asset class or for an asset will be forecasted using Time Series Model.
11	Maintenance & Repair Summary of an Asset Maintenance & Repair Summary of an Asset (RH_SM_FAL_010_0016) Mean Time Between Failure(MTBF), Mean Time To Repair(MTTR)and Mean Down Time (MDT) are compared for different assets in same class.
12	Maintenance Personnel Utilization This report gives us the actual time spent on maintenance of a Work Order having worktype PM or EM or CM.
13	Mean Residual Life (MRL) Mean Residual Life (MRL) (ALC_002_MRL) This report is used to calculate Mean Residual Life (MRL) of an asset by using reliability and survival probability of that asset
14	Monitoring Maintenance Cost Using IR Chart Monitoring Maintenance Cost Using IR Chart (RH_SM_COS_001_0017) Preventive maintenance cost for an asset will be monitored for the selected interval using IR Chart.It compares the actual cost Vs Budgeted Cost.
15	Monitoring Number of Failures Using C chart Monitoring Number of Failures Using C chart (RH_SM_FAL_009_0015) "Number of failures for an asset are recorded for different time point. A center line, is the average number of failures, which is calculated from the data . Upper and lower control limits (sometimes called ""natural process limits"") that indicate the threshold at which the maintenance process is considered statistically 'unlikely'. Upper and lower warning limits, drawn as separate lines, typically two standard deviations above and below the center line. "
16	Monte Carlo Simulation to Forecast Failure Causes Monte Carlo Simulation to Forecast Failure Causes (RH_SM_FAL_002_0008) Monte Carlo Simulation will be used to forecast causes of failure by simulation time to failure for an asset.
17	Optimum PM Interval Optimum PM Interval (RH_SM_PM_001_0001) Optimum PM Interval will be estimated based on the failure History of an asset.It will save additional cost on Time based PM's.
18	Pareto Analysis Pareto Analysis (RH_SM_FAL_005_0011) The purpose of Pareto Analysis Technique is to provide a means for identifying the key failures causes that have the highest occurrences in the selected interval to enable prioritization and focus on failure causes to aid in the failure analysis. •Find all the failures for the asset •Prepare the frequency distribution of failure cause and count •Find the Percent and Cum percent for frequency •Draw the Pareto Chart •Mark a horizontal line at 80% on Y – axis. Report the failure causes which contributes 80% of failures.
19	Performance Monitoring Performance Monitoring (PM_024) This report is used to show crew id or department-wise manpower usage, equipment downtime, # of breakdowns and also calculate % PM slippage.
20	Reliability & Availability of an Asset Reliability & Availability of an Asset (RH_SM_REL_001_0005) The report monitors and projects the reliability growth or performance of existing plant improvement, correlation of operational events against reliability, and forecast of failure rates by CROWAMSAA method.

1  2	All Asset Life Cycle Calculator Failure Analysis Inventory Life Cycle Cost Planning PM & PdM Reliability Resources Mgmt.