Constructed and implemented an enhanced Maintenance Management Operating System (MMOS) for FMS Diesel Mobile Maintenance (5)

Improved Planning System and Supply Chain Stockout Model

Maintenance

Mining and Metals

Mexico

Download Business Case

Keywords

MOS
Availability
MTBF
MTTR
Performance Management
CMMS Data Improvement
Effective Inspections
Bad Actor Management
Shift Change Management
Work Management Process (planning)
Supply Chain Stockout Alarm System
Pre-PM
PM Routines
SMART PM
5´s
Pit Stop Green Flag System
Flexibility Matrix

Driver Goal

To improve efficiency, predictability and reliability within the Mobile Maintenance area and equipment.
To improve Maintenance planning and operational effectiveness.
The delivery of the training and coaching required to enable the changes in behavior needed to ensure the sustainability of the operational improvements.

Results
Up to Week 16

Achieved Short range drilling availability to 93% for June. 9 points above the target, and long range drilling availability to 87% for June. 3 points above the target.
Achieved MTBF 17 hours for June. 5 points above target.
Early Shifts Inspection Program has generated 44 minute average of additional potential scoop utilization.
3.33% of real utilization for Scoops generated by improved shift management initiatives.
Stablished a 40 min std effective inspections.
Achieved 100% lubrication compliance for drills for the first time and 100% for scoops for 3 weeks.
Manloading has raised to 77% avg. from 40% before generating 700 MH avg of real executed hours.
100% Pre-PM and Perfect PM compliance for equipment.

Issue
Planning area was only planning for 62% of the available man hours of the crew. The man-hour source to assign preventive work, was based on standard times that did not reflected real times of execution. (Variability was 20% between plan vs actual man hours).

Solution Approach
Boosted proper manloading and raised to 78% when building the 10 day cycle plan. Based on the Bad Actor Management Methodology, the plan is filled out with relevant work for focused equipment. Less reactive work and more preventive and programmed corrective work is being executed.

Actions Taken

Daily PM / CM Compliance tool installed for supervisory force behavioral change and leverage the sense of urgency within the whole crews. Increased from 40% to 80% daily compliance for the last week of July.
Relevant work in a 10 day cycle has been loaded to the plan impacting the performance and reliability of different equipment.
Weekly attainment metric also installed achieved 83% for the last week in July.
With a man load plan of 91%, we have achieved 791 hours of real executed work.
Introduced daily intern-shift planner and supervisor meeting enhancing communication and increased effectiveness related to Work Order Cycle and Parts.
Planner Routine was generated and socialized. Still there is a yellow flag due to the fact that some of the new activities related to the new processes don´t fit timewise. A need of reinforcement by bringing interns to help the team prevails.

Second Issue

Based on The Team observations during the Feasibility Study, Supervisors spent the largest portion of their shift searching for, getting, and delivering parts to the Maintenance Crews, or Admin. time on work orders. Sometimes SAP system reported existence of an item that was actually not in inventory.

Because parts and materials are not often kit and staged, Crew Members and Supervisors are often spending NVA time looking for parts and materials.

Actions Taken

Contributed to Min-Max definition for Sandvik Stock (Strategic and Non strategic Parts).
Stockout model implemented for stockout risk periodical analysis.The model interacts within the 8 week PM projection for Preventive Maintenance.This model was also used for Sandvik consignment parts.
Thanks to the model no lack of parts for Hourly PM for equipment has been raised.
Finally, developed some inventory control studies in which the opportunity of lower inventory levels by $1M, with the same level of service at 99%.
Service level is set to 99%. This represents a 1% likelihood of stockout of any given part based on the standard deviations of statistical historical consumption patterns and lead times.