Overview and Case Studies SMS Spares Management Software

Overview and Case Studies SMS – Spares Management Software 1

Spares Management Software (SMS) Optimization criteria Non-Repairable Spares Interval Stock Reliability Instant. Stock Reliability Optimal Cost Minimization Requirement Spares Availability Stock Supportability Remaining Life 2

# items in service Repairable Spares Failures time stock failed units repaired units Repair shop 3

Criteria for Decision Making 1. Instant reliability 2. Interval reliability 3. Cost minimization 4. (Process) Availability 4

Scenario • Plant has 62 electric motors on their conveyor systems (Mining company) • MTBReplacements of motors is 3000 days (8 years) • Planning horizon is 1825 days (5 years) • Cost of spare motor is 15, 000 $ • Value of unused spare is 10, 000 $ • Cost of emergency spare is 75, 000 $ • MTTRepair a motor is 80 days • Cost of plant downtime for a single motor is 1000 $ per day • Holding cost of a spare is 4. 11 $ per day (10% of value of part/annum) QUESTION: HOW MANY SPARE PARTS TO STOCK? 5

Results: Repairable Parts Electric motors • Interval reliability: 95% reliability requires 7 spares • Instant reliability: 95% reliability requires 4 spares • Cost minimization: requires 6 spares. Associated plant availability is 100. 00% • Availability of 95%: requires 0 spares. Associated electric motor availability is 97. 4% [Note: If availability of 99% was required (rather than the specified 95%) then spares required would be 2] 6

Reference Case Population 100 transformers Failure Rate Repair Time 0. 005 failures/transformer/yr 1 yr Replacement Time 0. 001 yr Interval 1 yr 7

Repairable Instantaneous Reliability Vary Spares 1 0. 99 0. 98 Reliability 0. 97 0. 96 0. 95 0. 94 0. 93 0. 92 0. 91 0. 9 1 2 3 4 5 Spares 8

Additional Cases Case studies: 1. Fume fan shaft, blast furnace in a steel operation: non-repairable part, decision support 2. Power train component, haul trucks: repairable parts, multiple criteria 3. Frigate control system: supportability interval 9

1. Fume fan shaft – steel mill § Spares provisioning optimization project • • • Part: fume fan shaft used in a Blast Furnace Decision: should there be 0 or 1 spares? Complication: • Part has long lifespan (25 -40 years). • Long lead time (22 weeks). • If part fails, results are catastrophic (loss of almost $6 million per week). • Inventories are trying to be minimized. SMS was used to quantify the risk involved in not having a spare Decision support 10

How many spares – Fume fan shaft? 11

2. Repairable components – haul trucks § Open pit mining operation in South America § Haul truck power train component: COMPONENT X 12

Repairable components - Data / 1 General § 6, 600 operating hours per truck per year (average fleet utilization) § Preventive replacement policy at 9, 000 operating hours in place Time to replacement § Two parameter Weibull distribution, fitted using Weibull++ • 171 events: 86 failures, 85 suspensions (preventive replacements) • Beta = 0. 8565 • Eta = 14, 650 operating hours • Mean time to replacement = 6, 420. 3 operating hours 13

Repairable components - Data / 2 Time to repair § Based on estimations provided by maintenance personnel § Estimated at MTTR = 452 operating hours Cost of downtime and holding costs § Downtime: estimated using operational indicators (value of lost production, $2, 173. 3 / op. hour) § Holding: 25% of the value of the part per annum ($1. 51/ op. hour) 14

Repairable components - Data Summary Parameter Value Number of components in operation 78 MTBReplacements (μ) 6420. 3 (op. hours) Planning horizon (T) 6600 (op. hours) MTTRepair (μR) 452 (op. hours) Holding cost for one spare $1. 51 per op. hour (25% of value of part/annum) Cost of plant downtime for a single component $2173. 3 per op. hour SMS can perform the optimization based on four criteria 15

Repairable components - Results Case & Optimization criteria Optimal Stock level Associated Values Interval Reliability (goal = 95%) 15 Reliability = 98. 05% (for stock=14, Rel. =94. 99%) Instantaneous Reliability (goal = 95%) 10 Reliability = 97. 53% (for stock=9, Rel. =94. 75%) Availability (goal = 99%) 6 Availability = 99. 14 % Cost minimization 14 Total cost per unit time = $23 Inst. Reliability = 99. 94% 16

4. Frigate control system – supportability intervals (S. I. ) § Determination of supportability intervals • • • Several electronic components – control system Parts no longer available - discontinued Decision: how long can we support the operation of the system using only the current stock? (achieving the desired reliability of the stock) 17

Case Study – Supportability Interval (S. I. ) § Summary of Data Supportability interval (RUL of current stock) can be rapidly calculated using SMS – NEWLY ADDED FEATURE 18

Case Study (S. I. ) / 2 § Results Supportability for the system is influenced by the (shortest) supportability for any of its critical parts 19

Case Study (S. I. ) / 3 § Informed decisions for: • • • Adequate timing for replacement of current system Placement of final orders for discontinued parts Maximum supportability interval for current stock – procurement planning 20

Thank you 21