Winter Simulation Presentation: Simio/Deloitte Project



Identifying Cost Reduction and Performance Improvement Opportunities Through Simulation

by Ethan Brown
Deloitte Consulting LLP
December 14th, 2009

To download a PDF version of this presentation, click here.


Client dynamics

  • Client was facing higher costs and large amounts of capital tied up as inventory
  • Production line was struggling to produce current required volumes and showed signs of being unable to produce targeted levels of projected volume
  • Operating expenses were increasing due to constant overtime requirements
  • Client desired a way to reduce cost from the process, reduce inventory, but increase the production capacity to eliminate overtime and position the company to attain future production goals

Project team constraints

  • New manufacturing environment and industry
  • Four week duration from start-to-finish to:
    • Understand the business
    • Identify opportunities to improve the process
    • Learn a new simulation package and model the current process and potential improvements
  • An “alpha” version of the Simio software package

Manufacturing process overview

manufacturing example

Process complexities requiring modeling

  • Multiple production schedules are utilized
  • Kitting units
  • Assembly line moved at the pace of the slowest unit
  • Some resources were shared between equipment
  • Differing processing times
  • Varying hours of operation

Defined key hypotheses for modeling

Hypotheses to improve throughput and reduce WIP:

  1. Operations baseline: developing a functional model that mimics the process
  2. Schedule Integration: aligning / streamlining the schedule
  3. Kitting Availability: increased kitting frequency to reduce WIP on the line and to reduce the frequency of kits being
    delayed or delivered incomplete
  4. Part Presentation: improving how parts were kitted to the line to improve the speed of picking / using the part
  5. Workforce reduction: that fewer people were required than were currently utilized on the line

Demonstration of model

Results of the simulation

The four modeled improvements resulted in ~40% increase in throughput and ~35% decrease in WIP inventory.


Avg. Throughput Avg. WIP
Volume Change Volume Change
Baseline Performance 202 N/A 566 N/A
Schedule Integration 247 ↑ 22% 358 ↓ 37%
Kitting Availability 271 ↑10% 361 ↑1%
Part Presentation 285 ↑5% 363 ↑1%

Benefits of using Simio

  • Free-form structure of Simio
  • Powerful Standard Library
  • Customization with Add-on processes
  • “No code” object enhancements
  • Capability to define any mathematical KPIs
  • Advanced Ribbon” GUI
  • Experiments with multi-processor support
  • Model within model functionality
  • Integrated 3D Animation

Modeling challenges within consulting engagements

The use of simulation in a consulting environment posed several challenges:

  • Providing an accurate baseline of the process in order to gain confidence in predictive simulations
  • Identifying / modeling improvement initiatives within the shortened window of consulting engagements
  • Developing a model that is impenetrable to inquisitive review

Lessons learned

We identified several actions that could increase the speed / probability of acceptance:

  • White-board the model and walk client participants through the approach
  • Incorporate local programming talent
  • Utilize formerly constructed client simulation models
  • Complex is not always better