Accelerate Lean Results with Simulation!

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Generis – 2015 American Manufacturing Summit
Bruce Gladwin, ProModel Corporation
bgladwin@promodel.com

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 Introductions: Who, What & Why
 Evolution of (Lean) Process Analytics
 Simulation-based “Living VSMs”
◦ Understanding the “Physics of the Process”
 The Virtual Kaizen: your insurance policy
 Introducing Modeling & Sustaining the Gain

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 Bruce Gladwin – fellow pilgrim on the Lean journey
 28 years in process analysis and improvement
◦ Hughes Aircraft – Industrial Engineer Role
◦ General Electric R&D – Six Sigma Black Belt
 ProModel Corporation – Orem, Utah
◦ Simulation Trainer & Consultant
◦ Product Manager, Process Simulation Tool
◦ Currently VP, Modeling Services Team

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 What?
◦ How modeling tools, specifically discrete-event simulation,
can improve & accelerate your Lean journey
 Why?
◦ “The times they are a changin” – Bob Dylan
◦ Early modeling tools were not for “the faint of heart”
◦ Advances in simulation technology have put this valuable
technology within reach of more and more Lean practitioners
 Many tools today are “fill in the blank”, no programming required!

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 Learning to See – Lean Enterprise Institute

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Learning to See: © 1998 LEI, Inc., pp. 32-33

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Learning to See: © 1998 LEI, Inc., pp. 78-79

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 Value Stream Map
◦ Static model that describes
the states of current and/or
future processes
◦ Tells what is happening in the
process now and what the
process could be later
◦ Typically reports on lead time
and value added time
◦ Requires general information
regarding material arrivals,
operation times, labor and
equipment availability.
 e.g. average time = 15 sec
 Process Simulation
◦ Dynamic model that predicts the
behavior of current and/or future
processes
◦ Tells why a process behaves the
way it does or how it could behave
in the future
◦ Reports on throughput, inventory,
lead times, VA, NVA and resource
utilization
◦ Requires specific information about
material arrivals, batch constraints,
operation times, labor and
equipment uptime & availability,
transportation methods and times,
and any other capacity constraints.
◦ e.g. Time = T(5,10,25) sec

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Non-functioning
Recirculation
Loop for empty
Tub carriers

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Repairing the
Recirculation
Loop allowed
more WIP which
was key to fixing
problem

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Throughput
Up 37% !!
WIP also
Up 37% !!

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Interdependencies
Variation
SIMULATE
Use Simulation When You Cannot Ignore Variation and Interdependencies
Static
Tools
SPREADSHEET
ANALYSIS
MONTE-CARLO
SIMULATION
(Crystal Ball)
OPTIMIZATION ALGORITHMS (LP, MIP)

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Using “Averages” can be dangerous.
How much
Risk can
you afford
to take?

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Trying to optimize a
complex mfg system
is like trying to solve
the Rubic’s cube.
Simulation can
help understand
the trade-offs!!
Maximize Throughput
Reduce Cycle Time
Reduce Inventory
Minimize P&E
Interdependencies

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Exercise 1
…
from
Process
Simulator
Basics
Training
Course
Activity
Worker
Work Unit
(Exit)
5 minute
Process Time
100% Resource
Availability
Deterministic
Example
Activity 2
Worker 2
Work Unit 2
(Exit)
U(5,1) minute
Process Time
100% Resource
Availability
Stochastic
Example
Activity 3
Worker 3
Work Unit 3
(Exit)
U(4,1) minute
Process Time
80% Resource
Availability
Stochastic
Example with
Uncertainty
Activity 4
Worker 4
Work Unit 4
(Exit)
U(4,1) minute
Process Time
80% Resource
Availability
Assembly Opn
Stochastic
Example with
Uncertainty and
Interdependency
Activity 4A
Worker 4A
Work Unit 4A
BA
C D
Arrival Rate = 1 unit every 5 minutes
Identical for every arrival stream
No variation

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Results
Are
Striking!
30 Replications:
40 hr Comparison of
System A to System D
Throughput: - 4.6%
Avg Queue: + 14x
Avg Cycle: + 15x

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 A Virtual Kaizen is simply using simulation first to
better understand the “Physics of the Process”…
 Then design the improved process, to produce the
desired outputs, within expect levels of variation…
 All in a risk free environment
◦ No interruptions to the existing line
◦ No need to make physical rearrangements (yet)
◦ Ability to ask “What If”

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 Founded in 1975 by former Westinghouse engineers
 Ownership: privately held by founders
 Location: Pittsburgh area
 Employees: 150 total (50 salary, 100 hourly)
 Products:
◦ Mechanical Switches for Electric Utility Grids
◦ Automatic Distribution Motor Operators (ADMO)
 Allows remote control of switches by utility personnel

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Vertical Switch
V2-C (copper)
Center Break Switch
CB-A (aluminum)
6’
6’
Switches = 50% Revenues

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 Privately held, debt-free, profitable business with little
competition from low cost countries (for now).
 Capacity constrained. The market would buy every
additional unit that they could produce.
 Each additional unit sold will contribute about $5k-
$10k to their bottom line.
 Want to maximize 1st shift capacity before adding
additional 2nd shift operations.
 Considering 30,000 sq ft expansion to their existing
plant, at a cost of $1M.

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Eliminate or Reduce the Risk through a “Virtual
Kaizen” using Simulation Technology.

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 Value stream mapping
 Work standardization
 Point of use storage
 Single Piece Flow
 Visual management (Subassembly Feeder Lines)
 Kanban (pull) production (Subassembly Area)
 Setup reduction (Fabrication Area)
 Total productive maintenance (Fabrication Area)

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 Simulation proved to be an accurate tool for modeling
the current state Vertical Switch Assembly process
 A Future-State model using Lean Production concepts
proved to be far more efficient
◦ 20% improvement in product throughput!
◦ 67% reduction in average unit cycle time!
◦ 50% reduction in floor space requirements!
◦ Elimination of need for 2nd shift!

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 Identify the best opportunities
◦ Good ROI potential
 Every additional unit produced can be sold
◦ (Fairly) Low Risk
 Use a Sensei with years of modeling experience
 Involve all stakeholders, especially line operators
whenever possible
 Be patient and allow your team time to develop
modeling skillset. Make modeling a part of every
major process change.

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 Update the models regularly so they are always
available to predict the future
◦ More & better data results in better decisions
 Link to real-time data sources
◦ More & better data results in more accurate results
◦ Strategic Analysis becomes Tactical Analysis

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Generis – 2015 American Manufacturing Summit
Bruce Gladwin, ProModel Corporation
bgladwin@promodel.com