Operational Excellence foundations

What is Operational Excellence?

Simply put, it is better, faster, and cheaper. Better. 

Better quality of products and services, better processes, better user experience, and better value. Better in whatever's relevant and important.

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Key Concepts and Tools

• Process Stakeholders and SIPOC
• VOC, CTQ, and metrics
• Kano Model
• Variation
• Quality is assured at the source.
• Error Proofing or Poka-Yoke
• Lean Principles
• Process Mapping
• FMEA
• Control Plan

Implementing Operational Excellence

Alignment of all employees

Choose the right methodology

Audits to sustain Operational Excellence

Lean Day 3

VSM in the Service environment

Case study: Medical billing company wants to improve the utilization of employees and improve their resolution time of the claims.

Step 1: Write down the Process Steps (As-Is)

Step 2: Enter the PR (effort) for each step and capture the no. of outstanding req. at each stage.

Step 3: Note the Agents and Waiting Time at each stage.

Step 4: Enter the Individual and Summary table.

Step 5: Kaizen Burst (identify the improvement)

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3 Step approach to reduce NVA in the Service industry:

Eliminate > Improve> Automate

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Create Flow and Respond to Pull

Create flow:

Value Stream Design (VSD).

Single Piece Flow

SMED 

Line Balancing

Respond to Pull:

Kanban

Just-In-Time (JIT)

Heijunka (Production leveling)

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Additional Lean Tools

Spaghetti Diagram

TPM (Total Productive Maintainance)

OEE (Overall Equipment Effectiveness)

OEE 6 big losses

ANDON

Visual Factory

Visual management

Gemba

Hoshin Kenri (Policy Deployment)

Cellular Manufacturing

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LEAN Ends

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Lean Day 2

Principles of Lean

1. Identify Customers and Specify Value   (Customer Value Checklist)

2. Map the Value Stream                             (VSM As-Is )

3. Create Flow

4. Respond to Pull

5. Pursue Perfection

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VSM terminologies

CT (Cycle Time)                = Actual Process Time + In-built delay time.

TPT (Throughput time)     = CT + Queue Time+ Move Time+ Inspection Time + Waiting

FPY (First Pass Yield)        = Total good output / Total Input

RTY (Rolled ThruPut Yield) =  FPY (Process 1) x FPY (Process 2) .......... x FPY (Process N)

LT (Lead Time)                     =  Customer IN  to Customer OUT time.

Change Over time (CO)        = Time taken to change over from one type to another type.

WIP  (Work In Progress)        = Time when Work Started but not completed yet.

Customer Takt time                = Total available working time / Customer demand (# of units).

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VA, NVA, and BVA

Process Efficiency (PE)  = VA x 100 / VA + NVA

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VSM:

Steps in Value Stream Mapping:

0. Select product family (choose the product family as per Customer Takt time requirement)
1. Collect customer information (product family, volume, delivery frequency).
2. Tour the plant to identify & map the sequence of the main process.
3. Draw supplier information, collect data for critical parts, map the process flow
4. Draw information flow (Production schedule, communication system, interaction, ordering forecast)
5.Start collecting data from the last process in the sequence & fill out the data boxes, count inventory & map inventory locations.
6. Draw material flow & process interaction (Push, Pull, etc.)
7. Calculate Value Added, Non-Value Added, Process Efficiency.
8. Analyze each activity.
9. Identify Kaizen points

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Lean Day 1

LEAN is a systematic method for reducing/eliminating waste within a process.

WASTE is an activity that does not add value to the customers.

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5S :

Sort

Set in order

Shine

Standardize

Sustain

Understand by examples: 5S in Service and IT industries

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3 enemies of Lean

3M:

Muri: Overburden

Mura: Inconsistency

Muda: Waste

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Types of Wastes:

DOWNTIME:

Defects                           (Solve by Six Sigma, 7 QC, PDCA)

Overproduction             (Solve by Kanban)

Waiting                          (Solve by VSM)

Non-Utilized resources  (Solve by Gemba walk, Andon, Involvement)

Transportation                (Solve by Spaghetti diagram, VSM)

Inventory                        (Solve by Pull System, Kanban cards) 

Motion                            (Solve by Spaghetti diagram, VSM)

Extra Processing             (Solve by understanding ROI, VSM)

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Reasons for Wastes: 

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Waste Examples in the Service industry

Transport

• IT/Service tickets going through multiple hands – customer, onsite coordinator, offshore teams

(L1, L2)

• Re-assignment to the right groups because of wrong allocation first time

• Ticket containing insufficient information leading to queries and multiple hand-offs

Inventory

• The backlog of Tickets waiting to be worked on

• Tickets pending for user clarifications

• Tickets waiting to be picked up at the beginning of the day

Motion

• Seeking information from a colleague (SOP, document, email, etc.)

• Engineer searching for information in email/share point sites / calling colleagues

Waiting

• Waiting for customer feedback, information, resources

• Waiting for completion of predecessor tasks, clarification on requirements

• Delay / Lack of user response

• Ticket/Change Request waiting in queue to be attended by assigned engineer

Over-processing

• Multiple/Unnecessary reviews of the same ticket to ensure better quality

• QC of noncritical parameters

Over-production

• Creating reports no one requires & with no value adds

• Providing “Value Adding features” when not required for the customer

• Printing counterparty confirmation though it’s available by email

Defects & Rework 

• Poor documentation & non updated SOP’s

• Re-open tickets

• Incomplete documentation (Knowledge Management document not updated)

Non-Utilized resources

• Not involving the resources which have the critical information

• L2 Engineer utilized to perform L1 tasks

• L1 Engineer is not utilized to potential

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Hypothesis Testing notes

Hypothesis Testing notes:

As the Confidence Interval (CI) decreases the Range of data falling inside it also reduces. 

for example : Mean = 9.9515

CI 95% = 9.73 - 10.16 = Range 0.43

CI 75% = 9.82 - 10.07 = 0.25

CI 25% = 9.91 - 9.98 =   0.07

CI 1 %  = 9.951-9.952= 0.001

Also, when we have large sample size the CI range will be lesser as compared to small sample size.

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Significance level(alpha)  = 1 - Confidence interval.

if my CI is 95% then my Significance level (a) = 0.05

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Continuous Probability Distribution: Brandon

1. Uniform Distributions:

Example: A bus arrives at a bus stop daily between 11:25 to 11:35 am. There is an equal probability of reaching between each minute within those 10 minutes.

- A Coin flip has only 2 outcomes. no more than 2 outcomes can be there.

- A single dice can have maximum 6 outcomes.

DISCRETE PROB. Distribution

CONTINUOUS PROB. Distribution

Problem:

Z Distribution or Normal Distribution is where MEAN = 0 and Standard Deviation = 1

3. To Z or to T ?:

4. Daily Stock return analysis:

5. Is my Data Normal?:

Always look at data Graphically first.

SOURCE: Brandon Foltz

Process Capability indices

The basic Process Capability indices commonly used are Cp, Cpk, Cpm

Cp = VOC/ VOP = Tolerance/Natural Process variation = USL - LSL/ 6 std. dev.

• Cp values greater than or equal to 1 indicates the process is technically capable.
• Cp value equal to 2 is said to represent 6 sigma performance.

However, Cp index is limited in its use since it does not address centering of a process relative to the specification limits. For that reason Cpk was developed.

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Cpk = minimum (Cp lower , Cp upper)

• Cp lower = mean - LSL / 3 std dev.
• Cp upper = USL - mean / 3 std dev.
• Cpk determines the proximity of process mean to the nearest Specification limit.
• Also, at-least one specification limit must be stated in order to compute Cpk value.
• Cpk values of 1.33 or 1.67 are commonly set as goals since they provide some room for the process to drift in relation to the nominal setting

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Cpm, also known as process capability index of mean.

It is an index that accounts for the location of the process average relative to target value and is defined as.

where, T = target value (typically center of Tolerance)

• When the process average and target values are equal, the Cpm = Cpk.
• When the process average drifts from the target value, the Cpm is less than Cpk.