Performance Monitoring - Texas Tech University
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Transcript Performance Monitoring - Texas Tech University
Performance Monitoring
what is it, why do it, how does it work
Including an example of a collaborative workflow
approach to performance monitoring
1
The Six Sigma Process
Define
Measure how we’re doing
what’s important
3. Analyze the Current Process
2. Form Team and Scope the Proj ect
I nput
Identify Customers
and Requirements
Team Charter
Input
Supplier
Reqmt.
Measures
1. Identify Opportunities
Identify
Key
Variables
O utputs
Customers
Value
Measures
Establish
Process
Baseline
Establish
Process
Priorities
Quality
Cost
Time
Align Goals and Resources with Customer Requirements
Type
Map Product Flow
O ut put
W ax gr ade
Am t wax
Char ge r at e
Agit speed
Rxn t em p
Pr essur e
Air f low
% O2 in air
Viscosit y
W ax t em p
SO P
Cont r
Cont r
Cont r
Cont r
Cont r
Cont r
Noise
Noise
Noise
AN t ar get
Agit speed *
Tem per at ur e
Pr essur e *
Air f low *
% O2 in air
Air t em p
Air hum idit y
SO P
Cont r
*Cont r
Cont r
Cont r
Noise
Cont r
Noise
Pr ep t im e
Pr epar e React or
Acid num ber
Viscosit y
Char ge m elt ed wax
React or t em p
Br ing t o r eact ion t em p Tem p pr of ile
HT coef f
O xi di ze
Put in set point s
Sam ple hour ly
M onit or acid num ber
I nput
Type
Agit speed
Tem per at ur e
Pr essur e
Air f lo w
Cont r
Cont r
Cont r
Cont r
Put in set poin t s
% O2 in air
Nois e
Slo wly r educe pr ess
Air t em p
Cont r
4
2
1
O xid t im e
Acid num ber
Color
Viscosit y
React or t em p
Tem p pr of ile
O f f gas f low
O f f gas com p
HT coef f
Resp t im e
3
Product/Process Flow Summary and Analysis
Type:
Step
Operation ¶
Decision u
Delay ð
O ut put
Cust.
Rec.
Value
Intrin- Right
sic
First
Time
Distance
Time
T Q C
St ab t im e
Acid num ber
Colo r
Vis cos it y
St abi l i ze
React or t em p
M onit or t em p
Tem p pr of ile
O f f gas f lo w
O f f gas com p
HT coef f
MSE; Gauge R&R
LSL
2
4. Define Desired Outcomes
USL
Critical Measures and
Goals
100
1
C 0
4
50
-1
-2
In d e x
0
1 0
2 0
3 0
4 0
20 30 40 50 60 70 80 90 100 110
Normal
Total Distance
STRAP
Select Projects Critical to Customer and Business
As Is
Raw Cycle Time
X Factor 3
Analyze
what’s wrong
Mfg
N VA Ti me
Pr ocess Toler ance
11. 4481
14. 7185
I
I
I
I
A
D E
B
C
D
E
A
Activity Based
Management
B
C
D
Brainstorm Potential
Root Causes
E
Lean Enterprise
Pro c e s s /P ro d u c t
F a ilu re Mo d e s a n d Effe c ts An a ly s is
(F MEA)
P re p a re d b y :
P a g e _ _ _ _ o f_ _ _ _
F M E A D a te (O rig )_ _ _ _ _ _ _ _ _ _ _ _ _ _ (R e v )_ _ _ _ _ _ _ _ _ _ _ _ _
S
P o te n tia lF a ilu re M o d eP o te n tia lF a ilu re E fe c ts E
V
P o te n tia lC a u s e s
O
C
C
C u re n tC o n tro ls
D
E
T
R
P
N
A c tio n s
R e c o m m e n d e dR e s p .
S
A c tio n s T a k e nE
V
O
C
C
D
E
T
R
P
N
W h a tis th e In w h a tw a y s d o e s W
th he aK tise h
ty e m
i p a c o
t n h
t e K e yW h a tc a u s e s th e K e y In p u Wto hg ao ta e
r th e e x is tin g c o n tro s
l a n d W h a ta re th e a c tio n s W
fo hr o s e W h a ta re th e c o m p le te d
p ro c e s s s Inte pp u/ tg o w o
r n g ?
O u tp u tV a ria b le s (C u s to m e r w ro n g ?
p ro c e d u re s (in s p e c tio n a n d e
t s e
rt) d u c in g th e o c c Ru era sn pc oe n s aib cle tio n s ta k e n w ith th e
In p u tu n d e r
R e q u ire m e n ts o
) rin e
t rn a l
th a tp re v e n te ith th e c a u s e o rth e
o fth e C a u s e ,o r fo rth e
re c a lc u la te d B
R e
P N ?
in v e s tig a tio n ?
r q u re
e
i me n s
t ?
F a ilu re M o dS eh ?o u ld in c lu d e a n
im p ro v in g d e te c retio cn o? m m e n d e sd u re to in c lu d e
S O P n u m b e r.
S h o u ld h a v e a c tioa nc stio n ? c o m p le tio n m o n th /y e a r
o n ly o n h ig h R P N 's o r
e a s y fix e s .
0
0
$ p er Co st Driver
0
0
0
0
16
0
64
6. Prioritize, Plan and Test
Proposed Solutions
0
PROC
0
CHM
0
0
0
0
ELEV
0
0
48
0
0
0
0
0
MEM
0
9. Acknow ledge Team and
Com m unicate Results
32
0
0
0
OTHER
0
ABM
Decision Matrix
Explore Process Data
Data Collection Plan
Key Ou tp u tVariab les(C u sto merReq u iremen ts):
Solution I mpact
8
4
10
Box Plots
Strong Positive Correlation
TAKT Time
3 .5
110
Time Cos t
2
10
1
2
6
1
100
Output
80
70
Y = 9.77271 + 0.745022X
60
R-Squared = 0.876
50
40
1.
Ho wMeasu red
Wh en Measu red
Ho wMeasu red
Wh en Measu red
Valu e
Ho wMeasu red
Wh en Measu red
L ev el1
1
2
3
Un co n tro led In p u tVariab les("No ise"):
1
2
3
4
5
Co n tro led In p u tVariab les:
O
u
t
p
u
t
1
90
G O AL
Competitive
Advantage
($$$$)
Ship
Prioritize Causes
FMEA
Effect
Scatter Plots
Sa les
St Dev: 0. 54507
QC
P ro c e s s o r
P ro d u c tN a m e :
TEAM RESULTS
14
Mfg
R e s p o n s ib le :
P ro c e s s
S te p /In p u t
Project Report
13
CSR
H o w S e v e re is h
t e
e fe c to th e
c u s o tm e r?
C
C a teg o ry
Should B e
I
16
Specif icat ions
12
l l
Ship
Ca p a b i l i ty P l o t
Capabilit y Hist ogr am
I
H o w o fte n d o e s
c a u s e o rF M o c c u r?
B
Time
Costs
A
Takt
l l
QC
5. Identify Root Causes &
Proposed Solutions
Time
NVA $ = P ro cess Ba sed
COP Q
l
CSR
H o w w e lc a n y o u
d e te c tc a u s e o rF M ?
Cost
Pa reto C ha rt
Sa les
GOA L
8
Quality
Establish Entitlement
Process Capability
L ev el2
1
2
3
4
5
2 .5
Ov eralS amp lin g P lan :
1 .5
30
2.
40
50
60
70
80
90
100
110
1
120
2
Shif t 1
Input
Run Chart
Basic DOE
Pull System
GOA L
1.
8. Measure Progress and Hold Gains
2.
7. Refine and Implement Solutions
Machine 1
O
u
t
p
u
t
Machine 2
x
1
1. 3/10 Install Heater
2. Regrind Blade
Revised Control Plan
FR & T
I and MR Chart for: %PDP
Process St ep
35
Individuals
Act ual
DPHM * 10
Target
800
Benchmark
O ut put
I nput
Process
Speci f i cat i on ( LSL,
USL, Target )
Cpk / Dat e
M easurement
Techni que
%R&R
P/ T
Sampl e
Si ze
Sampl e
Frequency
Cont rol
Met hod
PRIOR
OPERATION
x
2
Shift
NEXT
OPERATION
React i on Pl an
UCL=34.21
30
M U=29.85
25
LCL=25.49
Out look
700
Observation 0
Moving Range
600
500
TARGET = 385
400
20
40
60
80
100
120
7
6
5
4
3
2
1
0
UCL=5.356
Project Plan (Gantt Chart)
Training & Procedures
R=1.639
LCL=0.000
300
BENCHMARK = 200
200
M TW H F S
100
Low Fl ow
0
140
Task
Who
Earliest Start
4/1
6/2
8/3
Hi gh Temp.
N
Act ual
D
J
F
N
D
J
560
540
520
M
A
M
F
M
A
490
490
440
M
J
J
J
J
Hi gh Press.
Sl udge
Out look
Control to guarantee performance Improve
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by fixing what’s wrong
Decision
Support
Layer
(Alert Mgr)
Decide
Monitoring
Layer
(Scouts, +)
Orient
Decision Support Model
Plant
Op Mode /
Op Context
Measure
Set
Expectation
C
Detect
Deviations
Aggregate
Decision UI
Info
S
Decide
Action
Assess
Impact
I
Diagnosis,
Prognosis
F
Workflow
Act
A
Action Layer
(ERP, DCS,
CMMS)
Plan &
Schedule
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Execute
Confirm, or
iterate
Notifications
Close out,
update
Core Process
The breakthrough is the technology that enables the
situations management process to be productive
Plant
Information &
access
Monitor &
alert
Resolve
Verify, assess
& learn
Isolate faults
In the past….
The situations management
process has had very
limited productivity.
It lacked the enabling
technology to conduct the
role of equipment in
productive capacity.
Assess
consequences
Action
Process
change
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CMMS
Decisions for
action
CMMS = computerized maintenance
management system
Collaborative Manufacturing
See www.cpfr.org for more
5
Collaborative Business Model - HPI
Manufacture /
Manufacturing Business
Development Activities
Create Joint Business Plan
Create Sales Forecast
Distribution Exception Triggers
Manufacture Exception Triggers
Identify Exceptions for Sales
Forecast
Distribution Decision
Support Data
Exception Items
Manufacture Decision
Resolve / Collaborate On
Exception items
Crude and
Production
Planning
Create Order Forecast
Order Forecast
Forecasting
POS Data
Support Data
Exception Criteria
Exception Criteria
Distributor or Distribution
Business Development
Activities
Planning
Develop Front-end Agreement
Frozen Forecast
Distribution Exception Triggers
Identify Exceptions For Order
Forecast
Distribution Decision
Resolve / Collaborate On
Exception Items
Support Data
Consumer
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Manufacture Decision
Support Data
Unresolved Supply Constraints
Produce Products
Order Generation
Order / PO
Product
Terminals
Manufacture Exception Triggers
Delivery Execution
Blending / Shipment
Execution
Order Filling Feedback
Replenishment
C-Store
Long
Term Short Term
Constraints
Step 1: Develop Front-End Agreement
• Purpose
• Distributor and Refiner establish the guidelines and rules for the relationship
• Addresses each party’s expectations and the actions/resources necessary for
success
• Includes the overall understanding and objective of the collaboration and the
empowerment of resources (both actions and commitment) to be employed
throughout
• Output
• A published agreement that provides a blueprint for beginning the
collaborative, defines the process in practical terms
• It also identifies the roles of each trading partner and how the performance of
each will be measured
• It spells out the readiness of each organization and the opportunities available
to maximize the benefits from their relationship
• It documents the commitment to pursuing a higher level of performance and
willingness to exchange knowledge and share in the risk
• Process and Data Inputs
• This step asks the partners for several key inputs which, taken together,
comprise the framework within which the forecast will be managed
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Step 1: Develop Front-End Agreement
Develop CPFR Agreement
& Statement
Determine CPFR Goals &
Objectives
I
Define Service and Ordering
Commitments
VI
II
Determine Resource
Involvement and Commitment
VII
III
Determine how to resolve
CPFR Disagreements VIII
Discuss Competencies,
Resources & Systems
Define collaboration points &
Responsible Business
Functions
IV
Determine review cycle for
The CPFR agreement
IX
Determine Information
Sharing Needs
Publish Front End
Agreement
V
Distributor
Activities
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Either / Joint
Activities
X
Refiner
Activities
Step 2: Create Joint Business Plan
• Purpose
• Partners exchange information about their corporate strategies and
business plans in order to collaborate on developing a joint business plan
• The partners first create a partnership strategy and then define category
roles, objectives, and tactics
• The product management profiles (e.g., Inventory replenishment levels,
shipment sizes, lead times, order intervals) for products to be
collaborated on are established
• This improves the overall quality of forecasting by including data from
both parties and facilitates communication and coordination across the
supply chain
• Output
• A mutually agreed-on joint business plan that clearly identifies the roles,
strategies, and tactics for the items to be collaborated on
• This is the cornerstone of the forecasting process greatly reducing
exceptions and the need for overly excessive collaboration
• Process and Data Inputs
• This step asks the partners to agree on strategies and tactics relative to
the replenishment items
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Step 2: Create Joint Business Plan
Identify Corporate
Strategies
I
Develop Partnership
Strategy
Develop Category Roles,
Objectives, Goals
Develop Business Plans
V
Agree Joint Business
Plan
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I
I
II
Develop Joint Category
Strategies / Tactics III
Develop Inventory
Management Profile
Distributor
Activities
Identify Corporate
Strategies
Develop Business Plans
V
IV
VI
Either / Joint
Activities
Refiner
Activities
Step 3: Create Sales Forecast
• Purpose
• In this step, retailer point of sale (POS) data, causal information, and
information on planned events are used to create a sales forecast that
supports the joint business plan. In different scenarios step is carried out
by the distributor or the manufacturer.
• Output
• A sales forecast is initially generated by one party, communicated to the
other party, and then used as a baseline for the creation of an order
forecast.
• Process and Data Inputs
• …
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Step 3: Create Sales Forecast
Analyze Current Joint
Business Plan
Collect & Analyze Point of
Sale Data
III
Analyze Causal
Information
I
II
Identify Planned Events:
Store Openings / Closings
Holidays
Promotions / Ads
New Products / Changes
IV
Generate Sales Forecast
VI
Distributor
Activities
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Identify Planned Events:
Promotions/Ads
New Products/Changes
Maintenance
Gather Exception
Resolution Data
(Output of Collaboration)
Either / Joint
Activities
V
Refiner
Activities
IV
Step 4: Identify Exceptions for Sales Forecast
• Purpose
• This step identifies the items that fall outside the sales forecast
constraints set jointly by the manufacturer and distributor.
• (The exception criteria for each item is agreed to in the front-end
agreement.)
• Output
• The output from this step is a list of exception items. This information is
necessary for Step 5.
• Process and Data Inputs
• …
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Step 4: Identify Exceptions for Sales Forecast
Retrieve Exception Criteria
Established by Front end
Agreement
I
Retrieve Sales Forecast
Identify Distributor
Changes / Updates
Identify Refinery
Changes / Updates
II
II
Compare Order
Forecast to
Supply / Capacity III
Item
value outside of
Limits set by exception
Criteria value
Yes
IV
No
Item Identified as
An Exception Data
Item Identified as NOT
An Exception Data
Distributor
Activities
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Determine Impact on
Shipment Forecast and
Apply Constraints
III
Either / Joint
Activities
V
VI
Refiner
Activities
Step 5: Resolve/Collaborate on Exception Items
• Purpose
• Resolving sales forecast exceptions by querying shared data, email,
telephone conversations, meetings, and so on
• Submitting any resulting changes to the sales forecast
• Output
• Collaborative negotiations between the Distributor and the Refiner resolve
item exceptions and adjust forecast
• The increased real-time collaboration fosters effective joint decision and
increases confidence in the eventual committed order.
• Process and Data Inputs
• This step begins with the exception items identified in Step 4
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Step 5: Resolve/Collaborate on Exception Items
Item Identified as an
Exception Item
Retrieve Exception Items
and Decision Support
Data
Research exceptions
using Event Calendar &
Supporting InformationIII
Does Research
Yield Forecast
Changes /
Resolve
Exception
I
Research exceptions
using Event Calendar &
Supporting InformationIII
Select Desired Exception
Criteria / Values
II
No
Does Research
Yield Forecast
Changes /
Resolve
Exception
No
Heighten Collaboration
IV
IV
IV
Yes
Submit Changes to Sales
Forecast
Yes
V
Distributor
Activities
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Either / Joint
Activities
Refiner
Activities
Step 5: Resolve/Collaborate on Exception Items
Alerts & Notification (Equilon ESP)
KPI Exceptions (Conoco BM)
Item Identified as an
Exception Item
Supply Chain Modeling
Retrieve Exception Items
and Decision Support
Data
SAND
Production Planner
Research exceptions
using Event Calendar &
Supporting InformationIII
Collaborative Forecasting
I
Research exceptions
using Event Calendar &
Supporting InformationIII
Select Desired Exception
Criteria / Values
II
Uniformance.NET
Does Research
Yield Forecast
Changes /
Resolve
Exception
No
Does Research
Yield Forecast
Changes /
Resolve
Exception
No
Heighten Collaboration
IV
IV
IV
Yes
Submit Changes to Sales
Forecast
Yes
V
Collaborative Forecasting
Distributor
Activities
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Either / Joint
Activities
Refiner
Activities
Step 6: Create Order Forecast
• Purpose
• Combine POS data, causal information, and inventory strategies to
generate a specific order forecast that supports the shared sales forecast
and the joint business plan
• Actual volume numbers are time-phased and reflect inventory objectives
by product and receiving location
• The short-term portion of the forecast is used for order generation, while
the longer-term portion is used for planning
• Output
• A time-phased, netted order forecast that allows the refiner to allocate
production capacity against demand, while minimizing safety stock
• Gives the distributor increased confidence that orders will be delivered by
reducing the uncertainty between trading partners
• Inventory levels are decreased, and customer service responsiveness is
increased.
• A platform for continual improvement among the trading partners is
established.
• Process and Data Inputs
• …
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Step 6: Create Order Forecast
Analyze / Provide
Refinery historical
Demand & shipments VI
Provide Sales Forecast
I
Analyze / Provide capacity
limitations
VII
Provide POS data
II
Provide order forecast
Impact events
Retrieve additional product
Management data (frozen
Period, lead time,
Logistics data VIII
III
Provide inventory strategies
/ seasonality's
IV
Provide current inventory
Position: on hand, on order
In transit
V
Distributor
Activities
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Gather Exception
Resolution Data
(Output of collaboration)
Gather order filling/
Shipment execution data
IX
X
Create Order Forecast
XI
Either / Joint
Activities
Refiner
Activities
Step 7: Identify Exceptions for Order Forecast
• Purpose
• This step determines what items fall outside the order forecast constraints
set jointly by the manufacturer and distributor.
• Output
• The result is a list of exception items identified based on the
predetermined criteria established in the front-end agreement.
• Process and Data Inputs
• …
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Step 7: Identify Exceptions for Order Forecast
Retrieve Exception Criteria
Established by Front end
Agreement
I
Create Order Forecast
Identify Distributor
Changes / Updates
Identify Refinery
Changes / Updates
II
II
Compare Order
Forecast to
Supply / Capacity III
Item
value outside of
Limits set by exception
Criteria value
Yes
IV
No
Item Identified as
An Exception Data
Item Identified as NOT
An Exception Data
Distributor
Activities
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Determine Impact on
Shipment Forecast and
Apply Constraints
III
Either / Joint
Activities
V
VI
Refiner
Activities
Step 8: Resolve/Collaborate on Exception Items
• Purpose
• This step involves the process of investigating order forecast exceptions
through querying of shared data, email, telephone conversations,
meetings, and so on and submitting any resulting changes to the order
forecast.
• Output
• The results of this step are the output of the negotiation (if necessary)
between retailer and manufacturer and resolution of item exceptions,
which are then submitted as an adjusted forecast. The increased realtime collaboration enabled by CPFR facilitates effective joint decisionmaking and fosters confidence in the order that is eventually committed.
• Process and Data Inputs
• This step uses the exception item data generated by Step 7.
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Step 8: Resolve/Collaborate on Exception Items
Item identified as an
Exception item
Retrieve Exception Items
& Decision Support data
I
Research exceptions
Using Event Calendar &
Supporting Information
Does
Research yield
Forecast changes/
Resolve
exceptions
Yes
IV
III
No
Select desired
Exception criteria / values
II
Heighten
Collaboration (e.g.
Messaging, Phone
Call, Meeting)
Submit Changes to
Order Forecast
Distributor
Activities
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Either / Joint
Activities
V
Research exceptions
Using Event Calendar &
Supporting Information
Does
Research yield
No
Forecast changes/
Resolve
exceptions
IV
Yes
VI
Refiner
Activities
III
Step 9: Order Generation
• Purpose
• This last step marks the transformation of the order forecast into a
committed order
• Order generation can be handled by either the manufacturer or distributor
depending on competencies, systems, and resources
• Regardless of who completes this task, the created order is expected to
consume the forecast
• Output
• The result is a committed order generated directly from the frozen period
of the order forecast
• An order acknowledgment is sent as a result of the order.
• Process and Data Inputs
• …
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Step 9: Order Generation
Extract Frozen Forecast
Based on Time Fence
I
Deploy Frozen Forecast
To Order Generation
II
Create Order
III
Transmit Order
Acknowledgement
Distributor
Activities
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Either / Joint
Activities
Refiner
Activities
IV
Example: Event Calendar
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Honeywell Solution Footprint
Source
Make
Distribute
Consume
Supply Chain Optimization
Supply Chain Modeling & Simulation
Raw Material Planning
Capacity Planning
Collaborative Forecasting
SAND
Inventory Targeting
Indicates
partner
Solution
Indicates
Joint
Development
Indicates
Hi-Spec
Solution
ATP / CTP / PTP
CROSS
Production Planner
Distribution Planning
ASSAY
Refinery Sched.
Optimization
Terminal Automation
Blend Scheduling
Gas Lift Opt.
Blend Optimization
Comp. Opt.
Production Analyst
Pipeline Opt.
Quality Mgt.
Pipeline Modeling
Pipeline Opt.
Production Balance
Production Tracker
Multi-site Optimization
Real-Time Optimization
Asset Management & Decision Support
ABC / Alerts & Notifications / POS
Hi-Spec Uniformance & .NET eBusiness Infrastructure
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Organizing Principle
Using Manufacturing KPIs to focus project delivery on
a customer’s business goals, and organizing solutions
to deliver improvements to those KPIs
28
Organizing Principle
• Projects need an organizing principle to maximize the
•
•
effectiveness of individual efforts.
That organizing principle should be based around a clear
articulation of how our solutions provide measurable
benefits to customers
Once identified, these same measurements can be used
as feedback mechanisms to prioritize further investment
choices
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Organizing Principle
Customer
Business
Goals
Manufacturing
Performance
Indicators
Product
Selection
and Testing
Use Case
Description
Work breakdown
and cost estimate
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Investment
Proposal
To Management
Typical Business Goals
• Delivering products on a worldwide basis, regardless of
where the order is taken and where the product is
shipped
• Product quality must be consistent from all manufacturing sites
• Shorten time between order placement and product
delivery
• Quality must be repeatable and predictable, with the work
performed continually adjusted to meet demand
• Minimize the trade-off between productivity and agility
• to enable B2B e-commerce
• Deliver Regardless
top-tier customer
of howsatisfaction
the latest management fad is
phrased, manufacturing remains a job of doing
the boring repetitive stuff right
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Six Sigma
•
•
•
•
•
One can derive from these business goals a clear
motivation for improving quality
Delivering Six Sigma quality requires improvements in
both repeatability and predictability of an operation
With improvements in repeatability, manufacturing
capacity can be better utilized
• No reprocessing off-spec material
With improvements in predictability, many of the lags in
the manufacturing process can be removed
• No waiting for the Lab to certify that product is on spec
• No extended analysis required to decide whether to accept a
purchase order / place a bid for work
Without the lags in the manufacturing process, inventory
can be reduced, freeing up working capital
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Lower level business goals
• Accurate and timely KPIs
• Manufacturing KPIs calculated directly as data becomes available,
and variance from goals reported directly to managers of interest
• Remove verbal instructions and manual reporting from the work practices
• Operating orders derived electronically from the purchasing
orders, and delivered directly to process operators when needed
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Monitoring Manufacturing Performance
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Monitor manufacturing performance using Key
Performance Indicators
• Primary KPIs - Consequential
• Key variables that management consider to have a measurable impact on/relationship
to the bottom line
• Identify a problem may exist, but not where it came from
• Management will set stretch goals for these KPIs
• Secondary KPI’s - Causal
• These KPIs help identify the where to start looking for the causes of missed targets with
the primary KPIs’
• Usually require a comparison of expected (forecast) values with actual values (Plan vs
Actual)
• Often thought of as Production KPIs
• Six Sigma methodology focuses on improving standard deviation of delta, not absolute
value - I.e. Improve accuracy of forecasting and operation
• Tertiary KPIs - Controllable
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These KPIs track the fundamentals of the forecasting
Often thought of as Process KPIs, and tend to be quite large in number
Usually at the individual property level or control variable level
Compare forecast vs actual with historical expectations
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Monitoring Manufacturing Performance
• Primary KPIs for Batch Processes
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# of Batches run in a week
# of Batches requiring rework in a week
% Reactor Utilization Rate
% Batch rework per reactor
# Cycle time variance exceptions
Total inventory of work in progress
Lab utilization rate
Ranking of day relative to previous days
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Monitoring Manufacturing Performance
Batch Activity Template
Batch
Reaction
Charge-1
Certification
Charge-2
Pumpout
Time
Alternative
Batch
Reaction
Charge-1
Certification
Rework
Charge-2
Pumpout
Time
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Monitoring Manufacturing Performance
• Calculating Primary KPIs for Batch Processes
• # of Batches run
• When a batch starts, increment global batch counter
• A calculation tag calculates delta change during period (24 hrs)
• # of Batches requiring rework
• When a batch requires rework, increment global batch rework counter
• A calculation tag calculates delta change during period (24 hrs)
• % Batch rework
• calculation tag calculates 100*(delta batch count - delta rework count) / (delta
batch count)
• % Reactor Utilization Rate
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When a batch starts on a reactor, set reactor in use flag to true
When a batch ends on a reactor, set reactor in use flag to false
A calculation tag calculates percent in use during period (24 hrs)
A calculation tag calculates Sum (%ReactorUtilization) during period
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Monitoring Manufacturing Performance
• Calculating Primary KPIs for Batch Processes
• # Cycle time variance exceptions
• When a cycle time is outside variance limits, increment a cycle time exception
counter
• A calculation tag calculates delta exception count during period (24 hrs)
• % Batch rework per reactor
• When a batch starts, increment reactor batch counter
• When a batch requires rework, increment reactor batch rework counter
• calculation tag calculates (delta batch count - delta rework count) /100
• Total inventory of work in progress
• Sum of all tank inventory in tanks + sum of all transfers into reactors
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Monitoring Manufacturing Performance
• Calculating Primary KPIs for Batch Processes
• Lab utilization rate
• When a certification starts, increment global lab counter
• calculation tag calculates delta lab counter for period (1 hr)
• Ranking of day relative to previous days
• calculation tag calculates unified KPI
= A*#Batches + B*#Reworks + C*Sum(%ReactorUtil) + D*WorkInProgress
• Excel spreadsheet function calculates Percentage(UnifiedKPI) which ranks the
last 24 hr period versus comparable periods
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Monitoring Manufacturing Performance
• Secondary KPIs for Batch Processes
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Batch yield versus standard
Batch cycle time versus standard
Reaction cycle time versus standard
Certification cycle time versus standard
Cool-down cycle time versus standard
Pump-out cycle time versus standard
Raw material consumption vs recipe
Lab utilization rate forecast (requires scheduling tool)
Reactor utilization rate forecast (requires scheduling tool)
Schedule slippage (Batch start time vs Plan start time)
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Monitoring Manufacturing Performance
Batch Activity Template
Batch
Reaction
Charge-1
Certification
Charge-2
Pumpout
Time
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Monitoring Manufacturing Performance
Batch Activity to Event Relationships
Batch
Close Cycle Time (Batch)
Open Cycle Time (Batch)
Reaction
Close Cycle Time (Reaction)
Open Cycle Time (Reaction)
Certification
Close Cycle Time (Certification)
Open Cycle Time (Certification)
Pumpout
Charge-1
Close Tank Log
CloseCycleTimeCharge
Close Tank Log
Close Cycle Time (Pumpout)
Source Transfer Log
Dest Transfer Log
Open Cycle Time (Charge)
Source Transfer Log
Destination Transfer Log
Open Cycle Time (Pumpout)
Open Tank Log
Charge-2
Open Tank Log
Close Tank Log
Close Cycle Time (Charge)
Source Transfer Log
Destination Transfer Log
Open Cycle Time (Charge)
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Open Tank Log
Monitoring Manufacturing Performance
Log Name
Open Cycle Time
KPI Attributes
Activity Type
Schedule Slippage
Slippage SQC
Close Cycle Time
Activity Type
Task cycle time
Cycle time SQC
Open Tank Log
Inventory
Description
e.g. Batch, Certification
Plan ST vs Actual ST
Slippage within
tolerance
e.g. Batch, Certification
Actual ET – Actual ST
Cycle time within
tolerance
Initial inventory of tank
Close Tank Log
Inventory
Final inventory of tank
Source Material
Transfer
Volume
Volume transfer seen at
Source
Mass transfer seen at
Source
Volume transfer seen at
Destination
Mass transfer seen at
Destination
Mass
Destination Material Volume
Transfer
Mass
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Monitoring Manufacturing Performance
• Tertiary Batch Performance Monitors
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Individual transfer quantity balance, source vs destination
Recipe phase cycle time
Finished batch property vs specification limits
Finished batch property vs SQC limits
Finished batch property vs PCA/PLS forecast
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Monitoring Manufacturing Performance
• Primary KPIs for receiving and shipping
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% Order satisfied on time
% Order satisfied on quantity
% Orders shipped with optimal transportation
% Orders with safety compliance exceptions
% Orders incurring demurrage
$ Demurrage costs incurred
Loading area utilization rate
Unloading area utilization rate
Ranking of day relative to previous days operation
Month to date ranking relative to previous operation
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Monitoring Manufacturing Performance
Unload Activity Template
Unload
CheckIn
Certification
PumpOut
CheckOut
Time
Load Activity Template
Unload
CheckIn
PumpOut
CheckOut
Time
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Monitoring Manufacturing Performance
• Calculating primary KPIs for receiving and shipping
• % Order satisfied on time
• When an order begins, increment an order counter
• When an order slippage variance is detected, increment slippage variance
counter
• calculation tag calculates 100*(delta order counter - delta slippage counter) /
(delta order counter) for a given period
• % Order satisfied on quantity
• When an order quantity variance is detected, increment quantity variance
counter
• calculation tag calculates 100*(delta order counter - delta quantity counter) /
(delta order counter) for a given period
• % Orders shipped with optimal transportation
• When sub-optimal transportation is detected, increment transportation variance
counter
• calculation tag calculates 100*(delta order counter - delta transportation
counter) / (delta order counter) for a given period
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Monitoring Manufacturing Performance
• Calculating primary KPIs for receiving and shipping
• % Orders with safety compliance exceptions
• When a safety compliance exception is detected, increment safety exception
counter
• calculation tag calculates 100*(delta order counter - delta safety counter) /
(delta order counter) for a given period
• % Orders incurring demurrage
• When demurrage incident is detected, increment demurrage counter
• calculation tag calculates 100*(delta order counter - delta demurrage counter) /
(delta order counter) for a given period
• $ Demurrage costs incurred
• When demurrage incident is detected, calculate the demurrage cost for this
increment (cycle time - free time) * demurrage rate and add this to a
demurrage counter
• calculation tag calculates delta demurrage counter for a given period e.g. $/day
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Monitoring Manufacturing Performance
• Calculating primary KPIs for receiving and shipping
• Loading area utilization rate
• When a product receipt begins, set the Equipment In Use flag to True. When
the receipt ends, set the Equipment In Use flag to False.
• calculation tag calculates percent in use for a given period e.g. 24 hr
• Unloading area utilization rate
• When a product shipment begins, set the Equipment In Use flag to True.
When the receipt ends, set the Equipment In Use flag to False.
• calculation tag calculates percent in use for a given period e.g. 24 hr
• Ranking of day relative to previous days operation
• calculation tag calculates Shipment unified KPI
= A*#Shipments + B*$ShipDemurrage+C*Avg(%SEquipUtil)+D*WorkInProgress
• Excel spreadsheet function “Percentage(ShipUnifiedKPI)” which ranks the last
24 hr period versus comparable periods
• calculation tag calculates Receipt unified KPI
= A*#Receipts + B*$RecDemurrage+ C*Avg(%SEquipUtil) +D*WorkInProgress
• Excel spreadsheet function “Percentage(RecUnifiedKPI)” which ranks the last
24 hr period versus comparable periods
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Monitoring Manufacturing Performance
• Secondary level KPIs for shipping and receiving
• Order placement to delivery cycle time
• Time of vehicle/vessel on site
• Demurrage is time spent in excess of free-time
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Safety compliance reports (by order, by vessel and by supplier)
Certification cycle time
Plan vs actual order quantity
Vehicle/vessel preparation cycle time
Pumping cycle time
Individual transfer quantity balance, source vs destination
Vehicle/vessel check-out cycle time
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Monitoring Manufacturing Performance
Unload Activity Template
Unload
CheckIn
Certification
PumpOut
CheckOut
Time
Load Activity Template
Unload
CheckIn
PumpOut
CheckOut
Time
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Monitoring Manufacturing Performance
Unload Activity to Event Relationships
UnLoad
Close Cycle Time (UnLoad)
Open Cycle Time (UnLoad)
CheckIn
Close Cycle Time (CheckIn)
Open Cycle Time (CheckIn)
Pumpout
Close Tank Log
Close Cycle Time (Pumpout)
Source Transfer Log
Destination Transfer Log
Open Cycle Time (Pumpout)
Open Tank Log
CheckOut
Certification
Close Cycle Time (CheckOut)
Open Cycle Time (CheckOut)
Close Cycle Time (Certification)
Open Cycle Time (Certification)
Honeywell Proprietary & Confidential
Monitoring Manufacturing Performance
• Secondary level KPIs for shipping and receiving
• Order placement to delivery cycle time
• Time of vehicle/vessel on site
• Demurrage is time spent in excess of free-time
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Safety compliance reports (by order, by vessel and by supplier)
Certification cycle time
Plan vs actual order quantity
Vehicle/vessel preparation cycle time
Pumping cycle time
Individual transfer quantity balance, source vs destination
Vehicle/vessel check-out cycle time
Honeywell Proprietary & Confidential
Monitoring Manufacturing Performance
Log Name
Open Cycle Time
KPI Attributes
Activity Type
Schedule Slippage
Slippage SQC
Close Cycle Time
Activity Type
Task cycle time
Cycle time SQC
Open Tank Log
Inventory
Description
e.g. Load, Unload
Plan ST vs Actual ST
Slippage within
tolerance
e.g. Load, Unload
Actual ET – Actual ST
Cycle time within
tolerance
Initial inventory of tank
Close Tank Log
Inventory
Final inventory of tank
Source Material
Transfer
Volume
Volume transfer seen
at Source
Mass transfer seen at
Source
Volume transfer seen
at Destination
Mass transfer seen at
Destination
Mass
Destination Material Volume
Transfer
Mass
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The scenario
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Tank Pressure
Limit
Delay
Blend
Display graphic
Request
Collaboration
Check time
stamp of
lab sample
New Sample
Old Sample
Check
Sample
RVP
Within
Expectations
Check CDU
Outside
Expectations
Outside
Expectations
Caused by
excess air
Within
expectations
Check
stabilizer
Outside
Expectations
Within
Expectations
Fix Merox
Treater
Cause not
found, request
analysis
Assign
Reason Code
Find out
when it will
be stable
Soon
Delay
Blend
Late
Check
Shipping
Commitments
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Reschedule
Blends
Check unit
for overall stability
Are the major unit targets
and limits being satisfied
Stable
Check Unit
Summary
Do process trend lines indicate
a process disturbance
Check stream
detail display
Unit
Upset
Stream
Conditions
Outside expected
Region
For the stream in question
get detailed info on values
and expectations, limits etc.
Shows data from lab, PHD
and scheduling tool
Stream
OK
Check operator logs
Check Operator logs
Existing OPS
log indicates
cause
Request operator log
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No problem to report
Check operator logs
for indication of process
problems