application of lean in product and manufacturing … of lean in product and manufacturing...

W

HITE P

APER

Application of Lean in Product

and Manufacturing Engineering

Version 1.0January 2010

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Getting ready for PLM

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Contents

Abstract................................................................................................................... 5

Introduction ............................................................................................................ 5

Scope & Objective................................................................................................... 5

Scope ................................................................................................................................................ 5

Objective........................................................................................................................................... 6

Applicability of 'Lean' .............................................................................................. 6

Value and Value Stream.......................................................................................... 7

Value................................................................................................................................................. 7

Design Value Stream......................................................................................................................... 8

Elimination of NVAs .......................................................................................................................... 8

Waiting.............................................................................................................................................. 9

Conveyance & Hand‐off.................................................................................................................... 9

Correction ......................................................................................................................................... 9

Flow....................................................................................................................... 10

Continuous Integration & Validation.............................................................................................. 10

Workflow Automation .................................................................................................................... 11

Pull......................................................................................................................... 11

Simplify Design Modifications......................................................................................................... 11

Associative Change Propagation..................................................................................................... 12

Continuous Improvement..................................................................................... 12

Shortening the Iterations................................................................................................................ 12

Reducing Iteration Cycles ............................................................................................................... 13

Implementation .................................................................................................... 13

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Incremental Implementation.......................................................................................................... 13

Knowledge Utilization..................................................................................................................... 14

Conclusion............................................................................................................. 14

References ............................................................................................................ 15

About the Author .................................................................................................. 15

About Geometric .................................................................................................. 16

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Abstract

This whitepaper discusses 'Lean' to continuously enhance product and manufacturing

engineering processes. It explains application of 'Lean' principles to improve productivity, lead‐

time, and responsiveness to change through real life examples. To implement 'Lean' it proposes

an incremental and self‐ sustaining approach, supplemented by CAx automations and KBE.

Introduction

Shortening product development lead time, while reducing the cost and increasing reliability, is a

perpetual challenge of engineering. This, coupled with changing consumer needs, doesn’t make

product development any easier. While manufacturing function has embraced the lean

philosophy with relative ease and enthusiasm, it is a struggle for engineering due to inherent

uncertainties.

This whitepaper discusses an approach to continually enhance the effectiveness and efficiency of

product development. We believe the first step is always to get the process right, before

deploying tools and technologies to run it better. We have also tried to illustrate the power

technology tools bring to make product development 'Lean'.

Scope & Objective

This paper focuses on engineering pieces of product development with an objective that is

defined from the product development context.

Scope Engineering functions define component specifications and manufacturing process in product

development. 'Product and Manufacturing Engineering' contribute in excess of 80% towards the

product development costs; and includes geometry creation and consumption across different

engineering sub‐functions.

Define Develop CommercializeServices & Support

RetireProduct Lifecycle

System Engineering

Design & Verification

Mfg. Planning & Tooling

Process Planning

EngineeringActivity

Planning & Ideation Production

Product Development

Product Engineering

Manufacturing Engineering

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This white paper is around product and manufacturing engineering, with focus on component

development. For remaining part of the white paper this scope is referred as 'Engineering

Activity'.

Objective

Component development matures through iterative development, which can be represented by

a spiral moving toward center. Time taken to traverse the spiral is lead‐ time and length of the

spiral is the total effort. At any point radius represents flexibility to modify the design.

Optimal Design

From this analogy, objectives of lean implementation are defined as

• Shortening the total spiral length to reduce the efforts.

• Reduce total time of traversal on spiral to reduce the lead‐time.

• Increasing flexibility to adapt the spiral for shift in spiral center.

• Get more insight from each revolution, to gradually reduce number of revolutions.

Applicability of 'Lean'

'Lean' is a generic philosophy. Various organizations have successfully applied 'Lean' to activities

ranging from a specific task to enterprise level. Commonly described 'Lean' principles are

• Specify value from the standpoint of the end customer

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• Identify all steps in value stream and eliminate steps that do not create value

• Follow value‐creation steps to achieve a smooth value flow toward the customer

• Let customers pull value from the next upstream activity

• Eliminate further waste and pursue perfection through continuous improvement

Due to inherent variations in engineering activity, it is thought that 'Lean' can not be applied in

engineering. But various references suggest sizeable opportunities in multiple pockets.

• Engineering jobs spend 60% of the lead time in waiting

• 40% of the engineering hours are pure waste

• 72% of product quality issues can be traced to design process

Engineering is combination of craft and science, which includes creative and repetitive tasks.

'Leaning' repetitive tasks offers larger opportunities for improvement in engineering activity.

'Lean' can be applied to the spiral of engineering activity to achieve the defined objectives. The

'Value & Value Stream' can be used to define contributions expected from each task, and trim

'Waste' segments to reduce length of each revolution. The 'Flow' principle can be used to

eliminate blockages and speed‐up flow on spiral, reducing the total traversal time. 'Pull' increases

flexibility for shift in spiral center to allow late changes in the requirement. 'Continuous

Improvement' is used to increase efficiency and effectivness of each cycle to reduce number of

revolutions.

Value and Value Stream

'Value' is providing right product / service at right time and at right price, as determined by the

customer. Value Stream Mapping (VSM) is used to capture sequence of tasks and segregate them

into Value‐ Add and Non‐ Value‐ Adds (VA / NVA), thereby helping to eliminate Non‐ Value‐ Add

tasks.

Value

Any activity / effort that can be directly traced to improving the product is said to be value

adding (VA), anything else is non value adding (NVA). Idea of Lean is to reduce the amount of

time and effort spent on NVA. Some activities affect the product directly, and some others will

improve the enterprise’s ability to continually better the product.

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• Foresee issues to reduce risk • CAE / CFD analysis • Expert reviews

• Material choices • Define shape and dimensions

• Define process to deliver product

• Manufacturing planning • Tooling design

Value to Product

• Specification for functional performance • Understanding of trade‐offs • Feasible / Infeasible trade‐offs • Cost / Quality implications

• Experience gained by engineers

• Insight to handle complex tasks • Best‐practices about usage of tools

• Understanding of process‐dynamics

• Project Management data

• Tool / process enhancement needs

Knowledge for Enterprise

Design Value Stream

Engineering activity presents unique challenges in application of VSM, due to concurrent tasks

and iterations. This can be tackled by creating a map for a typical iteration and by mapping

concurrencies and sub‐branches of VSM. The mapping follows the development beyond

organizational boundaries.

Elimination of NVAs

'Lean' defines seven sources of waste ‐ overproduction, waiting, conveyance, inventory,

processing, motion, and corrections. Eliminating these sources reduces the total work content. If

elimination is not feasible, counter measures should be used to reduce its impact.

The engineering activity has all sources of waste in different forms, but various surveys show that

waiting, conveyance and correction contribute to the majority of waste.

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Waiting

Engineering jobs wait for capacity (e.g. experts time for review, computing capacity) to handle

the job, or for information required to proceed with the job. Due to inherent variability in

engineering activity, it is not easy to ensure access to right capacity merely through coordination

and synchronization. So it becomes necessary to find creative ways to increase the capacity in a

flexible manner.

Conveyance & Hand‐off

At every touch‐point defined in the VSM, engineering hours are spent on model derivation to suit

the downstream function. For e.g.:

• Analysis idealization and boundary condition placement requires manual effort on part of

the analyst

• Manufacturing model requires various modifications for manufacturing allowances, and to

generate bill of process

Inherent differences between various functions make it impossible to eliminate model derivation.

But derivation effort can be reduced by 20‐50% by utilities to assist the derivation process.

An automation utility to evaluate weight and CG at each section will reduce the analyst’s effort of ‘Model Derivation’. It saves the cost of analysis, and simultaneously eliminates errors associated with manual work.

Structural analysis of airplane wing must account for self‐weight of the wing structure. Analyst cuts the wing geometry in multiple sections to evaluate weight and center‐of‐gravity (CG) of each section as part of ‘Model Derivation’.

Correction

Design mistakes result in design corrections, which is waste according to lean principles. 'Lean'

advocates mistake‐proofing to avoid or to warn against mistakes. In engineering activity, 40% of

the iterations are due to errors in physical design. Hence, physical design should be a target for

mistake‐proofing.

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Check surfaces for min bend radius

Mistakes in HVAC geometry can be eliminated by two mistake‐proofing methods –

• Check and restrict selection of inputs. Assuming that the duct is created by

sweeping, check if path curves have lines and arcs only.

• Validate output at exit and raise error / warning, if there are any non‐planer and

non‐cylindrical surfaces , or if there are any minimum bend radius violations.

Due to manufacturing constraints HVAC duct geometries must be planer / cylindrical. Any other geometry will result in change requests from manufacturing.

HVAC Duct manufactured from

Sheetmetal Path curve consists of lines & arcs

Flow

'Flow' reduces lead‐time, by running value‐creating steps in tighter sequence. In manufacturing,

flow reduces lead‐time by eliminating batch and achieving single piece flow.

In engineering activity, batches occur at integration and validation points. The batches can be

reduced, if design flows in smaller increments by continuous integration and validation, and

increased capacity through workflow automation.

Continuous Integration & Validation

A typical product development integrates the system at fixed time intervals. Reducing effort of

integration allows gradually switching to continuous integration.

Digital build is a task to assemble complete product to check for contact and clash problems.

In the past, digital build was done manually at program milestones. Today, it is triggered from PLM, as a nightly job. Batch job assembles the product and checks for clashes. Digital build is further leveraged for weights and inertia calculations, which can be used in the dynamic analysis.

Increased frequency of integration results in early problem detection and access to latest data for various validations.

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Continuous integration is not sufficient without validation at each integration. The validations

come in form of reviews by experts or precise verification by analysts. Both validations have

external dependencies, which result in batch validations.

An incremental validation that evolves from thumb‐rules to precise validations, integrated in

design environment reduces the dependencies. Engineers can use it for continuous validation, to

eliminate the batching.

Workflow Automation

Flow of engineering tasks is disrupted, when a task has to wait for the engineer's attention. This

can be tackled by triggering batch jobs during idle hours (e.g. night), at certain stage of PLM

workflow. Engineers can directly start with output of the batch job, and move the job to next

stage. This will accelerate flow of engineering job.

In the analysis cycle, design engineer submits analysis job and receives analysis report. Analyst prepares and runs the analysis, and analyzes results in post‐processors to prepare the report.

There are two waiting points – before and after the analysis. There is more waiting in analysis, since the analysis run is submitted as batch jobs. Total waiting time in analysis cycle can be a few days to a week.

If the manual tasks in preparation are eliminated, complete preparation and analysis run can

be triggered from PDM workflow, which can be run during the idle hours (e.g. at night).

Analyst can directly analyze the results and prepare report. This will reduce the waiting time

in one iteration – considering multiple iterations, it will be a great saving in the lead‐time.

Pull

Pull principle brings 'Responsiveness to Change' by aligning the system with variance in customer

requirements. In engineering, pull means quickly adapting component design to changes in

product requirements.

Simplify Design Modifications

Design edit is a complex task where engineers spend 80% of their efforts. Complexities of editing

slow change incorporation, which can be simplified by ‐

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• Deploying top‐down and bottom‐up design processes for managing design features, and

modularity to ensure right dependencies as well as flatten decision hierarchy during the

design process

• Supporting the right input methods to represent correct user intent. This reduces the

occurrences of design breaking, and subsequent rework during minor changes in the design.

• Enabling all design automations during edit scenario. Automation implementation may

become complex to support edits, but it makes design changes faster.

Capturing ‘User’s Intent’ at each design feature helps in seamless update in the design hierarchy. Wherever correct intent is compromised, the design structure can break, requiring manual correction.

In this demonstration, user wants to fillet top face of block as shown in red color. User quickly picks top four edges and fillets and achieves the result. This breaks the intent of ‘Face’, which will show up in modification. If design modification inserts a fillet and chamfer prior to this fillet , the update cycle will not pick the filleted and chamfered edges. Then fillet has to be modified manually, which makes edit cumbersome.

‘User Intent’ can be achieved by enforcing correct design methods and by enhancing the design tools to support the intent.

Associative Change Propagation

A quick design modification is not sufficient if it requires rework in downstream functions like

verification. Propagating design modifications can be simplified by maintaining feature

associativity across functions through simpler conventions (e.g. colors and persistent tags

assigned to geometries).

Continuous Improvement

To achieve full potential of 'Lean', multiple rounds of leaning are needed, with each round

eliminating newer wastes and flow disruptions. In addition, for iterative process, continuous

improvement can target reduction in iterative efforts by shortening iterations and reducing the

number of iterations.

Shortening the Iterations

Design optimization refines component design, and validates against targets. The ability to

validate the design early shortens the iteration, thereby, reducing the lead‐time and efforts.

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Iterative development for design optimization can be captured in Decision Structure Matrix

(DSM). DSM highlights frequent and long iterations, which can be shortened by moving critical

validations (e.g. DFx) closer to design creation.

Reducing Iteration Cycles

In iterative development, number of iterations depends on the starting parameters and the rate

of convergence. The number of iterations can be reduced by two approaches:

• Deploy predictive verification in form of design analytics. Analytics can be built from expert's

knowledge, empirical rules, engineering formulae, etc. It guides to design with less

possibility of failure in validations.

• Increase effectiveness of validations by extracting qualitative feedback. Validations typically

report only failure areas, whereas qualitative feedback points out sensitivity of design

towards constraint put by validations.

Implementation

We recommend incremental roll‐out of a long‐term implementation plan. Incremental roll‐out

brings quick results and creates assets, which can be leveraged for further improvements.

Through this approach, we have observed 30‐ 40% compression in lead‐time, and upto 40%

reduction of engineering efforts.

Incremental Implementation

Incremental approach consists of five steps for each round of implementation. Each round starts

with understanding of process and finishes with solutions developed and deployed. Subsequent

rounds identify more opportunities for improvement.

3. Solution IdeasScalability

Effort

Scalability

Power of Tools

1. Process Capture

• Design mistakes & rework

• Continuous integration / validation• Associative change propagation

2. Identify Opportunities

Continuous Improvement

4. Cost‐Benefit / Prioritization5. Develop & Deploy

Effort

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For better results through implementation, some of the points to ensure are ‐

• Involve engineering users from early stages of implementation, so that they can drive

continuous improvement

• Seek understanding of critical parameters that affect the product and how existing processes

achieve it

• Take view of complete workflow including various CAx and backbone PLM tools for effective

workflow automation

• Focus on solutions first, and then look at how 'Power of Tools' can help reach the solution

• Prefer solution in the form of toolbox of utilities for flexibility of usage and adaptability with

process changes

Knowledge Utilization

Cyclical implementation of 'Lean' brings deeper understanding of process, and builds assets of

automation utilities and knowledge. Effective utilization of these assets offers more

opportunities of improvement.

1. Task AutomationAutomate conveyance, motion and processing

2. Workflow AutomationConveyance triggered by PLM, during waiting time

3. Predictive AnalyticsAnalytics on performance and prediction of errors

Timeline

ProcessPredictability

Typical Benefits

Cycle‐TimeReduction

Productivity& Quality

We, therefore, propose a knowledge utilization framework to leverage assets for gradual

improvements in productivity, lead‐time, and predictability.

Conclusion

'Lean' offers multitude of opportunities to enhance an engineering activity. This white paper

discussed adoption of lean concepts in engineering activity, with examples from product and

manufacturing engineering.

Due to the complex nature of engineering full benefits of lean can not be derived from one time

implementation. Applying 'Lean' through incremental implementation approach will create

assets with attached benefits in the implementation cycle. A long term view of leveraging the

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assets will help extracting more benefits from the 'Lean' initiative, in terms of productivity,

reduction in lead‐ time, and predictability.

References

Lean Thinking: Banish Waste & Create Wealth in Your Corporation, James Womack and Daniel

Jones, Free Pres, 2003

The Toyota Way, Jeffrey Liker, The McGraw Hill Companies, 2004

Use of Dependency Structure Matrices for Product Development Cycle Time Reduction, Tyson

Browning, Fifth ISPE International Conference on Concurrent Engineering : Research and

Applications, 1998

Lean Product Development Flow, Bohdam Oppenheim, Systems Engineering, Vol. 7, No. 4, 2004

Application of Lean Principles in Software Development, Lokendra Singh Panwar, XLRI

Jamshedpur School of Business & Human Resources

Design process error‐proofing: Strategies for reducing quality loss in product development,

Lawrence Chao and Kosuke Ishii, ASME International Mechanical Engineering Congress and

Exposition, 2005

Risk Management in Product Engineering, Nikhil Shintre, Geometric Limited, 2008

About the Author

Nikhil Shintre is the Head of the CATIA Practice at Geometric. He has over 10.5 years of

experience in CAD application development and automation. Nikhil holds a Masters Degree in

Machine Design from the Indian Institute of Technology, Mumbai. He can be reached on

[email protected].

mailto:[email protected]

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About Geometric

Geometric is a specialist in the domain of engineering solutions, services and technologies. Its

portfolio of Global Engineering services and Digital Technology solutions for Product Lifecycle

Management (PLM) enables companies to formulate, implement, and execute glo bal

engineering and manufacturing strategies aimed at achieving greater efficiencies in the product

realization lifecycle.

Headquartered in Mumbai, India, Geometric was incorporated in 1994 and is listed on the

Bombay and National Stock Exchanges. The company recorded consolidated revenues of Rupees

5.98 billion (US Dollars 129.47 million) for the year ended March 2009. It employs close to 3000

people across 11 global delivery locations in the US, France, Romania, India, and China.

Geometric is assessed at SEI CMMI Level 5 for its software services and ISO 9001:2000 certified

for engineering operations. For further details, please visit www.geometricglobal.com.

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