Embark on a transformative journey with Al Shalloway in this compelling video presentation, where he delves into the art of problem-solving within Value Streams. As a seasoned expert in Lean-Agile practices, Al unravels the core principles essential for effective Value Stream management, guiding viewers through the identification and mitigation of common challenges. Gain insights into the influential factors shaping Value Streams and learn from real-world case studies and best practices. Whether you're a seasoned Agile practitioner or just starting your journey, Al Shalloway's expertise offers a roadmap to streamline processes, eliminate waste, and optimize the flow of value for enhanced organizational success.
Industrial Engineering is System Efficiency Engineering. It is Machine Effort and Human Effort Engineering. 2.57 Million Page View Blog. 200,000+ visitors. (17,000+ visitors in the current calendar year) Blog Provides Industrial Engineering Knowledge: Articles, Books, Case Studies, Course Pages and Materials, Lecture Notes, Project Reviews, Research Papers Study Materials, and Video Lectures. Blog provides full IE Online Course Notes
Thursday, November 30, 2023
ChatGPT - Engineering Innovation - Performance and Productivity Benefits
MODERN INDUSTRIAL ENGINEERING, PRODUCTIVITY MANAGEMENT, COST REDUCTION PRINCIPLES, FUNCTIONS AND FOCUS AREAS. Free Download
https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0
30 November 2023 - First year Anniversary of ChatGPT
ChatGPT is marking one year since its creation. How much more do we know about AI now?
By Liana Walker and Brianna Morris-Grant
Three billion people now have access to either ChatGPT or Copilot or to Bard, who are the big three chat AI bots.
Bloomberg reported that the AI generative industry will be worth $1.3 trillion over the next 10 years,.
https://www.bostonglobe.com/2023/11/29/business/chatgpt-one-year-anniversary/
last revised 29 Nov 2023 (this version, v2)]
ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
Hailin Chen, Fangkai Jiao, Xingxuan Li, Chengwei Qin, Mathieu Ravaut, Ruochen Zhao, Caiming Xiong, Shafiq Joty
Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement learning from human feedback, it showed that a model could answer human questions and follow instructions on a broad panel of tasks. Following this success, interests in LLMs have intensified, with new LLMs flourishing at frequent interval across academia and industry, including many start-ups focused on LLMs. While closed-source LLMs (e.g., OpenAI's GPT, Anthropic's Claude) generally outperform their open-source counterparts, the progress on the latter has been rapid with claims of achieving parity or even better on certain tasks. This has crucial implications not only on research but also on business. In this work, on the first anniversary of ChatGPT, we provide an exhaustive overview of this success, surveying all tasks where an open-source LLM has claimed to be on par or better than ChatGPT.
https://arxiv.org/abs/2311.16989
https://www.axios.com/2023/11/28/chat-gpt-one-year-anniversary-ai
Axios has local news sections - Austin is one location.
30 November 2022
Tweet by Sam Altman on Twitter
Job Shop - Industrial Engineering - Productivity Improvement - Cost Reduction
https://books.google.com/books?id=sAarCAAAQBAJ&pg=PA396&lpg=PA396#v=onepage&q&f=false
Case Study of HDS Division, Schlumberger
Summer of 1985
Time to Reform Job Shop Manufacturing
by James E. Ashton and Frank X. Cook, Jr.
From the Magazine (March–April 1989)
https://hbr.org/1989/03/time-to-reform-job-shop-manufacturing
Written instructions.
Schedule adherence
Bibliography
Lekan Olanrewaju
Jan 31, 2023 | 6 minutes read
Overcoming the Challenges of Job Shop Manufacturing
https://www.getmaintainx.com/blog/overcoming-the-challenges-of-job-shop-manufacturing/
Navigating High-Mix, Low-Volume Manufacturing
July 27, 2022
By Kip Hanson, Contributing Editor, SME Media
https://www.sme.org/technologies/articles/2022/july/navigating-high-mix-low-volume-manufacturing/
How to Make a Machine Shop Lean - Dr. Shahrukh Irani - Chapter Summary
https://nraoiekc.blogspot.com/2022/06/how-to-make-machine-shop-lean-dr.html
Home Concurrent Engineering: Tools and Technologies for Mechanical System Design Conference paper
Relationship Between Design for Manufacturing, a Responsive Manufacturing Approach, and Continuous Improvement
J. E. Ashton
Conference paper
Part of the NATO ASI Series book series (NATO ASI F,volume 108)
https://link.springer.com/chapter/10.1007/978-3-642-78119-3_17
Time to Reform Job Shop Manufacturing
by James E. Ashton and Frank X. Cook, Jr.
From the Magazine (March–April 1989)
https://hbr.org/1989/03/time-to-reform-job-shop-manufacturing
Ud. 30.11.2023
Pub. 11.7.2023
British Factory, Japanese Factory: National Diversity in Industrial Relations - Ronald Dore Book Information
British Factory, Japanese Factory: The Origins of National Diversity in Industrial Relations
Ronald Dore
University of California Press, 1973 - Industrial relations - 432 pages
The way that the Japanese work is often perceived as "different." The author here sets out to find how different and why. He is not interested in impressionistic East/West comparisons but in making a strict comparison of two Japanese factories with two British ones making similar products. The first half of his book illustrates the attitudes and assumptions that underline the "organization-oriented" system of Japan and the "market-oriented" system of Britain. Much can be said for the orderliness, the mutual consideration, with which the Japanese manage their affairs; but they pay a price--the sacrifice of individuality and of independence. The British preserve these virtues but, in doing so, they pay a price in suspicion, obstinacy, inertia, and what the author calls "a shifting mixture of complacency and national self-doubt." But the purpose of this book is not to judge but to explain--to give, as the author says, a causal account of the genesis of the reasons why there should be two all but identical processes of creating all but identical electric generators--two very different ways of ordering the social and economic relations among the people involved.
Preview
Twitter - X - Computing & Communication Cost Reduction - Cost Savings - Elon Musk
MODERN INDUSTRIAL ENGINEERING, PRODUCTIVITY MANAGEMENT, COST REDUCTION PRINCIPLES, FUNCTIONS AND FOCUS AREAS. Free Download.
https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0
X Shifts Media Processing from Cloud to On-Prem: Saves $60M
https://www.linkedin.com/pulse/x-shifts-media-processing-from-cloud-on-prem-saves-ks6oe/
https://www.linkedin.com/pulse/unlocking-efficiency-cost-savings-strategic-shift-from-ashvit--9wpfc/
https://www.cnbc.com/2022/11/03/musk-orders-twitter-to-cut-infrastructure-costs-by-1-billion-sources-say.html
X/Twitter claims $100m in annual savings after exiting Sacramento data center
Company also cites savings from cloud repatriation moves
October 31, 2023
August 15, 2023
How Much Does Twitter Spend On AWS And Google Cloud?
https://www.cloudzero.com/blog/twitter-aws/
Breaking Down the Cost of Cloud Computing in 2023
By
Linda Rosencrance
Published: 04 Nov 2022
Cost savings is one of the main reasons that companies decide to migrate to a cloud environment. Cloud computing can offer organizations potential financial advantages in a few ways; however, it's important to understand the full implications of cloud pricing, and how it can affect companies.
https://www.techtarget.com/whatis/Breaking-Down-the-Cost-of-Cloud-Computing
2015 Pdf KPMG
https://assets.kpmg.com/content/dam/kpmg/pdf/2015/11/cloud-economics.pdf
News - Miscellaneous Articles and Posts on Tesla
https://ilovetesla.com/
https://www.linkedin.com/in/garyzhou/
30 Nov 2023
Tesla Cybertruck delivery event in 4 minutes
____________________________
https://www.youtube.com/watch?v=BjxIyHp7wBc
____________________________
Elon Musk - Tesla Cybertruck deliveries event in Austin
PUBLISHED THU, NOV 30 20232:38 PM EST
https://ilovetesla.com/delorean-dmc-12-designer-gives-thumbs-up-to-tesla-cybertruck/
The Tesla Cybertruck is far from a normal vehicle in nearly every way you can assess it, but DeLorean DMC-12 designer Giorgetto Giugiaro gave the truck a nod of approval and gave Tesla props for thinking outside the box.
https://www.linkedin.com/posts/garyzhou_delorean-dmc-12-designer-gives-thumbs-up-activity-7130313857788428288-jziL
https://www.linkedin.com/posts/garrettech_tesla-reveals-everything-that-affects-its-activity-7130243434430279680-xf95
Tesla has allegedly been suppressing EV range complaints.
Sudhanshuman Naruka
Student at SVKM NMIMS Kirit P. Mehta School of Law
August 6, 2023
https://www.linkedin.com/pulse/tesla-has-allegedly-been-suppressing-ev-range-sudhanshuman-naruka/
Tesla leases space in Pune for its first office in India
Updated - August 03, 2023 at 09:47 AM.
The office space on lease has been taken at a starting monthly rent of ₹11.65 lakh
Tesla plans to roll out EVs at a starting price of ₹20 lakh in India:
https://www.thehindubusinessline.com/companies/tesla-leases-space-in-pune-for-its-first-office-in-india/article67149892.ece
https://www.linkedin.com/pulse/teslas-supply-chain-sujay-v/
https://www.linkedin.com/pulse/tesla-emerges-victorious-ev-charger-wars-earn-warns/
https://www.linkedin.com/pulse/article-tesla-bot-suryateja-kamma/
https://www.linkedin.com/posts/electrek_tesla-software-update-activity-7051249548580585472-lIIC
https://www.linkedin.com/posts/premsingh-rajput-528623209_tesla-revolutionizing-the-auto-industry-activity-7090187534973976576-naZA
https://www.linkedin.com/posts/muralitoday_rareearths-rareearthelements-electricmotors-activity-7037408350208233472-51Oo
2022
https://www.linkedin.com/posts/dbhati9_tesla-reportedly-partners-with-tsmc-for-next-generation-activity-7002832672267923456-a7_F
https://www.linkedin.com/posts/kumar-rikesh_tesla-semi-looks-incredible-as-an-electric-activity-7005037413483835392-fwom
2021
https://www.linkedin.com/posts/aryantandon_rivian-teslamotors-generalmotors-activity-6875038869310590976-qvpW
https://www.linkedin.com/pulse/elon-musks-tesla-stock-sales-demystified-ca-naman-gangwal-cpa/
Ud. 30.11.2023
Pub. 15.11.2023
Botswana - Industrial Engineering Education
Botswana
Bachelor of Engineering (Industrial Engineering)
https://www.ub.bw/programmes/engineering-and-technology/mechanical-engineering/bachelor-engineering-industrial-engineering
https://www.biust.ac.bw/biust-programmes/beng-industrial-manufacturing-engineering/
University Of Botswana Industrial Engineers Association - UBIEA
141 likes • 153 followers
?paipv=0&eav=AfYJevdzvcmQEHVlpWgHJ_td9OdGN8-41ygfvleAFYieFCFU2-21U_VQQLE7yWMjRe0&_rdr
How Industrial Engineering has affected my lifePOSTED ON DECEMBER 24, 2016 BY AAWSE_ADMIN
imag3531
Tumisang Orapeleng is a final year Industrial Engineering student at the University of Botswana. She is also working part-time at the Botswana Engineers Registration Board. She speaks about what has changed in her life since she started her course and where she believes her career is headed.
https://aawse.org/how-industrial-engineering-has-affected-my-life/
IEOM Botswana Chapter
Gaborone, Botswana
Founding Chair:
Dr. Jerekias Gandure
Associate Professor
Department of Mechanical Engineering
University of Botswana
Gaborone, Botswana
Phone: +267-3554421; fax: +267-3954902
E-mail: gandurej @ mopipi.ub.bw
Tuesday, November 28, 2023
Software Development Operation Process Chart - Analysis of Software Writing (Development) Operations - IT Industrial Engineering
2023 BEST E-Book on #IndustrialEngineering.
INTRODUCTION TO MODERN INDUSTRIAL ENGINEERING. Free Download.
https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0
Software Operation Process Chart for Software Process Improvement
Software Operation Process Chart contains two operations - Software Development and Software Testing. Both operations are analyzed for productivity improvement in industrial engineering of software development.
Information for Supporting Analysis of Software Development Operations
Unleashing developer productivity with generative AI
June 27, 2023 | Article
A McKinsey study shows that software developers can complete coding tasks up to twice as fast with generative AI. Four actions can maximize productivity and minimize risks.
Expediting manual and repetitive work.
Jump-starting the first draft of new code.
Accelerating updates to existing code.
Increasing developers’ ability to tackle new challenges.
McKinsey Developer Productivity Paper - Review
4 Oct 2023
https://dannorth.net/mckinsey-review/
Improving Software Developer Mental Well-Being and Productivity
September 19, 2023
https://www.informatics.uci.edu/8098-2/
AI & ML: The next generation of developer productivity
By Mike Loukides
August 15, 2023
https://www.oreilly.com/radar/the-next-generation-of-developer-productivity/
Waste Self-reporting for Software Development Productivity Improvement
Marc Sallin, Martin Kropp, Craig Anslow & Robert Biddle
Conference paper
Open Access
First Online: 20 May 2023
Part of the Lecture Notes in Business Information Processing book series (LNBIP,volume 475)
Agile Processes in Software Engineering and Extreme Programming Conference paper
Waste Categories incl. Measurement.
From: Waste Self-reporting for Software Development Productivity Improvement
Waste Category - Measurement and Unit
WC1 Building the wrong feature or product [5] Customer confidence (Likert-Scale)
WC2 Mismanaging the backlog [5] Time spent (h) & Delay (h)
WC3 Rework [5] Time spent (h)
WC4 Unnecessarily complex solutions [5] Time spent (h)
WC5 Extraneous cognitive load [5] Time spent (h)
WC6 Psychological distress [5] Stress (numerical rating scale)
WC7 Waiting/multitasking [5] Delay (h) & Context Switches (count)
WC8 Knowledge loss [5] Time spent (h)
WC9 Ineffective communication [5] Time spent (h)
WC10 Management & organizational aspect [19] Time spent (h) & Delay (h)
WC11 Manual work (new category) Time spent (h) & Delay (h)
WC12 Other duties (new category) Time spent (h)
https://link.springer.com/chapter/10.1007/978-3-031-33976-9_4
37 tips for improving productivity in software development teams
By
Daniel Beck
https://sprkl.dev/37-tips-for-improving-productivity-in-software-development-teams/
15 Key Software Development Metrics & KPIs for Measuring Engineering Productivity
28 April 2023 • 24 min read
Andrii Horiachko
Co-Founder at Softermii
Inside the World of Developer Productivity: Best Practices from Google
Vishal Pallerla•April 7, 2023
https://www.devzero.io/blog/inside-the-world-of-developer-productivity-best-practices-from-google
The Impact of AI on Developer Productivity:
Evidence from GitHub Copilot
Sida Peng,∗ Eirini Kalliamvakou, Peter Cihon, Mert Demirer
Feb 2023
https://arxiv.org/pdf/2302.06590.pdf
How To Optimize Developer Productivity During Times Of Financial Uncertainty
Ilan Peleg
Forbes Councils Member
Forbes Business Council
Jan 25, 2023
9 of the Best Productivity Tools for Developers in 2023
January 10, 2023
https://clickup.com/blog/best-productivity-tools-for-developers/
Unblocking Workflows: The 2023 Guide to Developer Productivity
What can you do to accelerate developer productivity in 2023?
Part 1: Key Productivity Challenges
Part 2: Developer Productivity Survey Results
Part 3: Improving Developer Productivity and Collaboration
Part 4: Improve Collaboration to Accelerate Productivity
What can you do to accelerate developer productivity in 2023
https://mattermost.com/guide-to-developer-productivity-2023/#what-can-you-do-to-accelerate-developer-productivity-in-2023
2020
Myths of Programmer Productivity
https://insights.sei.cmu.edu/documents/5690/2020_018_101_650692.pdf
2019
https://www.microsoft.com/en-us/research/video/productivity-in-software-development/
What Predicts Software Developers’ Productivity?
Emerson Murphy-Hill Ciera Jaspan Caitlin Sadowski David C. Shepherd Michael Phillips Collin Winter Andrea Knight Dolan Edward K. Smith Matthew A. Jorde
Transactions on Software Engineering (2019)
https://research.google/pubs/pub47853/
Defining Productivity in Software Engineering
Stefan Wagner & Florian Deissenboeck
Chapter
Open Access
First Online: 08 May 2019
https://link.springer.com/chapter/10.1007/978-1-4842-4221-6_4
2017
Study of Task Processes for Improving Programmer Productivity
by
Damodaram Kamma
PhD Thesis
2017
IIIT Delhi
2014
Study of Task Processes for Improving
Programmer Productivity
Damodaram Kamma
Indraprastha Institute of Information Technology, Delhi
Thesis Advisor: Prof. Pankaj Jalote
https://2014.icse-conferences.org/sites/default/files/downloads/Kamma.pdf
https://www.gartner.com/peer-community/post/how-measure-maximize-developer-productivity
https://www.researchgate.net/publication/279259268_Software_Developers'_Perceptions_of_Productivity
Improving speed and productivity of software development: a global survey of software developers
Publisher: IEEE
J.D. Blackburn; G.D. Scudder; L.N. Van Wassenhove
IEEE Transactions on Software Engineering ( Volume: 22, Issue: 12, December 1996)
https://ieeexplore.ieee.org/document/553636
UNDERSTANDING SOFTWARE PRODUCTIVITY
WALT SCACCHI
Information and Operations Management Department
School of Business Administration
University of Southern California
Los Angeles, CA 90089-1421, USA
(Appears in Advances in Software Engineering and Knowledge Engineering, D. Hurley (ed.),
Volume 4, pp. 37-70, (1995).
December 1994
https://ics.uci.edu/~wscacchi/Papers/Vintage/Software_Productivity.html
1992
1045-1992 - IEEE Standard for Software Productivity Metrics
https://ieeexplore.ieee.org/document/211732
What does this term, "productivity" of software development really mean?
https://www.andrews.edu/~vyhmeisr/papers/progprod.html
1988
Software Metrics
https://insights.sei.cmu.edu/library/software-metrics/
Software Operation Process Chart - Analysis of Software Testing Operations - IT Industrial Engineering
2023 BEST E-Book on #IndustrialEngineering.
INTRODUCTION TO MODERN INDUSTRIAL ENGINEERING. Free Download.
https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0
Software Operation Process Chart for Software Process Improvement
Software Operation Process Chart contains two operations - Software Development and Software Testing. Both operations are analyzed for productivity improvement in industrial engineering of software development.
What are the best practices for reducing the cost of software testing in large-scale projects?
1
Define clear testing goals and scope
2
Automate your testing as much as possible
3
Implement continuous testing and integration
4
Leverage cloud-based testing tools and services
5
Optimize your testing team and processes
6
Monitor and measure your testing performance and outcomes
Narayana Rao KVSS
Professor (Retired), NITIE - Now IIM Mumbai - Offering FREE IE ONLINE Course Notes
You can prepare a software operation process chart. Operation process chart is an industrial engineering tool to record the operations in a process. It records only two operations. In software operation process chart they will be development and test. All test operations in the chart are examined in the process improvement to first check whether they are effective. Then they are evaluated for efficiency. Automating them is an efficiency improvement step. The time and cost involved in each testing operation are also recorded in the chart to check whether new methods provide improvement or not.
https://www.linkedin.com/advice/0/what-best-practices-reducing-cost-software
Matthew Heusser is a consulting software tester and self-described software process naturalist who develops, tests and manages software projects. Matt is a contributing editor for Software Test & Quality Assurance Magazine and his blog “Creative Chaos
” focuses on software writing.
An elected member of the Board of Directors of the Association for Software Testing, Matt recently served as lead editor for “How to Reduce the Cost of Software Testing” (Taylor and Francis, 2011). You can follow Matt on Twitter @mheusser or email him.
1st Edition
How to Reduce the Cost of Software Testing
Edited By Matthew Heusser, Govind Kulkarni
Copyright 2012
Jun 21, 2022
Software testing cost estimation: how to optimize your QA budget
When you start a project, the software testing costs may frighten you off. In 2022, the average yearly salary of a QA Engineer in the USA reached $96k. It is essential for CTOs to find ways to optimize the testing budget. But how to cut costs without compromising on product quality?
How to Reduce Your Software Testing Costs by 35%
January 5, 2023 by Bindhu Charles Test Automation, Testing Agile Testing Strategy, AI based Testing Framework, Automation Solutions, Scaling Test Automation, Software Testing Costs, test automation framework, Test automation strategy
A set of ways to optimize the cost of Software Testing
Bechir Haribi
Lead System Engineer at NOFFZ Technologies
https://www.linkedin.com/pulse/set-ways-optimize-cost-software-testing-bechir-haribi/
Beyond Lean: Simulation in Practice - Charles R. Standridge - Book Information
Beyond Lean: Simulation in Practice, Second Edition
Charles R. Standridge Ph.D., Grand Valley State University
https://scholarworks.gvsu.edu/books/6/
https://scholarworks.gvsu.edu/cgi/viewcontent.cgi?article=1006&context=books
Lean Beyond Flow - Industrial Engineering
Lean theory is distilled from Toyota Production System by a team of MIT researchers.
Lean was coined by a researcher to characterise inventory in TPS as lean in contract the traditional inventory maintained in US automotive companies was termed bulk.
Toyota started utilizing lean inventories and made gains in productivity surpassing the labor productivity of US companies.
The MIT team came out with five principles to explain Lean system to be used by companies now to implement the best practice of Toyota.
The five principles are value, stream, flow, pull and perfection. All these five principles are related to flow. They actually identify inventories in the production system and try to reduce them. As inventories are reduced flow increases.
-----------------------
You can see the focus on flow in lean theory from this explanation by Kettering.
Understanding the Principle of Flow in Lean Manufacturing
Understand value from the customer perspective
Understand the Value Stream
Make the Value Stream Flow
Create Pull
Continuously Improve
Identifying the Seven Flows of Manufacturing
Mike Wroblewski, Senior Operations Consultant for Gemba Consulting, explains in his Reliable Plant blog, the Seven Flows of Manufacturing by his Japanese sensei, Nakao-san:
The flow of raw material
The flow of work-in-process
The flow of finished goods
The flow of operators
The flow of machines
The flow of information
The flow of engineering
Barriers to Flow
If you want to improve flow, first remove all barriers. Figliolino Venanzio, Founder of Lean Six Sigma University, outlines both physical and intangible barriers to flow:
Examples of Physical Barriers to Flow:
Distance: Rather than transporting individual items, they are collected and shipped as a group
Long Setup Times: When changing over tooling takes a long time, larger batches are run
Batch-Oriented Machines: Some machines are designed to be most efficient with large runs.
Poor Maintenance: Machines that break down frequently disrupt flow.
Examples of Intangible Barriers to Flow:
Unreliable Deliveries: When there is no trust that parts will arrive on time, extras are kept on hand
Unreliable Quality: If people think that many parts will be unsuitable or will require rework, extras will be kept on hand
Approval Processes: The approver is seldom standing by, so work is piled up until the next opportunity to get the go-ahead
Lack of Faith: Some people just don’t believe flow is possible, so don’t even try
Resistance to Change: Some people think flow might work, but like things to stay the same.
https://online.kettering.edu/news/understanding-principle-flow-lean-manufacturing
-----------------------
Industrial engineering is a discipline formally started as an academic branch in engineering in 1908. Its foundation is cost reduction of engineering products and products produced by machinery developed by engineers through productivity improvement. Initially the focus was on increasing speed of machines and understanding the maximum speed at which a human operator can work under various weights of load. The premise was that both managers and operators do not know the maximum speed at which work can be done and quality output produced. Also the speed should not damage machines and harm operators. Operators have to be comfortable working at the recommended speed of motions for hand and feet.
Beyond Lean: Advanced Principles of Productivity [Hypertherm with Kevin Duggan]
https://www.youtube.com/watch?v=n4AuprJ041M
https://www.youtube.com/@InstituteOpex
About
Institute for Operational Excellence
@InstituteOpex
‧
704 subscribers
‧
32 videos
The Institute for Operational Excellence is the leading educational center for organizations and individuals interested in learning how to evolve a lean enterprise into one that can achieve and sustain Operational Excellence.
Links
instituteopex.org
instituteopex.org
facebook.com/InstituteOpEx
twitter.com/InstituteOpEx
2023 Machine Shop Engineering, Technology & Industrial Engineering - Productivity Improvement & Cost Reduction News
https://mfgnewsweb.com/archives.aspx
Metal Working Equipment News
https://www.equipment-news.com/
Twitter Hashtag Machining
https://twitter.com/hashtag/Machining
Productivity Science of Machining - F.W. Taylor - Experiments and Results.
Free Download
Synera - Design to Cost Tool - Geometric Data Linked to Professional Costing Tools
The Low-Code Platform for Engineers
Model your product development steps in a simple visual editor and integrate the CAE tools you know and rely on.
Model-based approach
Transition from document-based engineering to model-based engineering and bring agility to your product development processes.
Contact
info@synera.io
+49 (0)421 2215 9700
Konsul-Smidt-Str. 8u
28217 Bremen
Germany
https://www.synera.io/focused-case-study/design-to-cost
https://www.synera.io/success-story/edag
Cost Engineering
Discover how Low-Code can revolutionize cost engineering and procurement. Streamline costing processes and align with sustainability objectives.
Download whitepaper
The path to a cost engineering revolution
Accelerate cost estimation & CO2 analysis time by 80% using Low-Code
Do you find yourself relying on historical costs that may no longer be relevant due to the absence of a rule-based framework? The challenges in today's cost engineering and procurement landscape are real. But there is a solution. This whitepaper introduces Low-Code, a universal language that unifies all tools and information sources relevant to cost engineering. With Low-Code, data moves effortlessly through a digital thread, making it easy for cost engineers and other departments to share data between different tools and systems. Say goodbye to suboptimal decisions and operational inefficiencies and hello to streamlined costing processes. It's time to revolutionize cost engineering and procurement.
Key takeaways
Low-Code can accelerate cost estimation and CO2 analysis time by 80%
Low-Code can help cost engineers align with sustainability objectives, such as adhering to CO2 emission standards
Traditional knowledge transfer processes in cost engineering can be inefficient and create information silos
Synera Run can democratize automation and bridge the gap between expertise and accessibility
The cost estimation process can be vulnerable to critical knowledge gaps when valuable knowledge is concentrated within a select few individuals
Who has to read it?
Cost Engineers
Engineering Managers
Business leaders
Download the whitepaper
Sunday, November 26, 2023
Engineering Optimization - A Bibliography
References from
Optimization of Part Consolidation for Minimum Production Costs and Time Using Additive Manufacturing
2019 paper
Zhenguo Nie, Sangjin Jung, Levent Burak Kara, Kate S. Whitefoot
Mechanical Engineering, Carnegie Mellon University
Engineering and Public Policy, Carnegie Mellon University
Pittsburgh, PA, USA
https://meche.engineering.cmu.edu/_files/images/research-groups/whitefoot-group/NJKW-OptPartConsolidation-JMD.pdf
References
[1] Yang, S., Talekar, T., Sulthan, M. A., and Zhao, Y. F.,
2017, "A Generic Sustainability Assessment Model towards
Consolidated Parts Fabricated by Additive Manufacturing
Process," Procedia manufacturing, 10, pp. 831-844.
[2] Yang, S., Tang, Y., and Zhao, Y. F., 2015, "A new part
consolidation method to embrace the design freedom of
additive manufacturing," Journal of Manufacturing Processes,
20, pp. 444-449.
[3] Yang, S., and Zhao, Y. F., 2015, "Additive manufacturingenabled design theory and methodology: a critical review,"
The International Journal of Advanced Manufacturing
Technology, 80(1), pp. 327-342.
[4] Hague, R., 2006, "Unlocking the design potential of rapid
manufacturing," Rapid manufacturing: an industrial revolution
for the digital age.
[5] Uriondo, A., Esperon-Miguez, M., and Perinpanayagam,
S., 2015, "The present and future of additive manufacturing in
the aerospace sector: A review of important aspects,"
Proceedings of the Institution of Mechanical Engineers, Part
G: Journal of Aerospace Engineering, 229(11), pp. 2132-2147.
[6] Wong, K. V., and Hernandez, A. J. I. M. E., 2012, "A
review of additive manufacturing," ISRN Mechanical
Engineering, 2012.
[7] Schmelzle, J., Kline, E. V., Dickman, C. J., Reutzel, E. W.,
Jones, G., and Simpson, T. W., 2015, "(Re) Designing for part
consolidation: understanding the challenges of metal additive
manufacturing," Journal of Mechanical Design, 137(11), p.
111404.
[8] Frey, D., Palladino, J., Sullivan, J., and Atherton, M.,
2007, "Part count and design of robust systems," Systems
engineering, 10(3), pp. 203-221.
[9] Türk, D.-A., Kussmaul, R., Zogg, M., Klahn, C.,
Leutenecker-Twelsiek, B., and Meboldt, M., 2017,
"Composites part production with additive manufacturing
technologies," Procedia CIRP, 66, pp. 306-311.
[10] Booker, J., Swift, K., and Brown, N., 2005, "Designing
for assembly quality: strategies, guidelines and techniques,"
Journal of Engineering design, 16(3), pp. 279-295.
[11] Boothroyd, G., Dewhurst, P., and Knight, W. A., 2001,
Product Design for Manufacture and Assembly, revised and
expanded, CRC press.
[12] Combemale, C., Whitefoot, K. S., Ales, L., and Fuchs, E.
R., 2018, "Not All Technological Change is Equal:
Disentangling Labor Demand Effects of Automation and Parts
Consolidation," Available at SSRN 3291686.
[13] Taufik, M., and Jain, P. K., 2013, "Role of build
orientation in layered manufacturing: a review," International
Journal of Manufacturing Technology and Management, 27(1-
3), pp. 47-73.
[14] Jibin, Z., "Determination of optimal build orientation
based on satisfactory degree theory for RPT," Proc. Computer
Aided Design and Computer Graphics, 2005. Ninth
International Conference on, IEEE, p. 6 pp.
[15] Thomas, D. S., and Gilbert, S. W., 2014, "Costs and cost
effectiveness of additive manufacturing," Special Publication,
NIST.
[16] Alexander, P., Allen, S., and Dutta, D., 1998, "Part
orientation and build cost determination in layered
manufacturing," Computer-Aided Design, 30(5), pp. 343-356.
[17] Langelaar, M., 2016, "Topology optimization of 3D selfsupporting structures for additive manufacturing," Additive
Manufacturing, 12, pp. 60-70.
[18] Leary, M., Merli, L., Torti, F., Mazur, M., and Brandt,
M., 2014, "Optimal topology for additive manufacture: a
method for enabling additive manufacture of support-free
optimal structures," Materials & Design, 63, pp. 67
8-690.
[19] Mirzendehdel, A. M., and Suresh, K., 2016, "Support
structure constrained topology optimization for additive
manufacturing," Computer-Aided Design, 81, pp. 1-13.
[20] Paul, R., and Anand, S., 2015, "Optimization of layered
manufacturing process for reducing form errors with minimal
support structures," Journal of Manufacturing Systems, 36, pp.
231-243.
[21] Vanek, J., Galicia, J. A. G., and Benes, B., "Clever
support: Efficient support structure generation for digital
fabrication," Proc. Computer graphics forum, Wiley Online
Library, pp. 117-125.
[22] Boothroyd, G., Dewhurst, P., and Knight, W. A., 2001,
Product Design for Manufacture and Assembly, CRC press.
[23] Yang, S., Santoro, F., and Zhao, Y. F., 2018, "Towards a
numerical approach of finding candidates for additive
manufacturing-enabled part consolidation," Journal of
mechanical design, 140(4), p. 041701.
[24] Chadha, C., Crowe, K., Carmen, C., and Patterson, A.,
2018, "Exploring an AM-enabled combination-of-functions
approach for modular product design," Designs, 2(4), p. 37.
[25] Yang, S., Santoro, F., Sulthan, M. A., and Zhao, Y. F.,
2019, "A numerical-based part consolidation candidate
detection approach with modularization considerations,"
Research in Engineering Design, 30(1), pp. 63-83.
[26] Nyaluke, A., Nasser, B., Leep, H. R., and Parsaei, H. R.,
1996, "Rapid prototyping work space optimization,"
Computers and industrial engineering, 31(1-2), pp. 103-106.
[27] Canellidis, V., Dedoussis, V., Mantzouratos, N., and
Sofianopoulou, S., 2006, "Pre-processing methodology for
optimizing stereolithography apparatus build performance,"
Computers in industry, 57(5), pp. 424-436.
[28] Wodziak, J. R., Fadel, G. M., and Kirschman, C., "A
genetic algorithm for optimizing multiple part placement to
reduce build time," Proc. Proceedings of the Fifth
International Conference on Rapid Prototyping, University of
Dayton Dayton, OH, pp. 201-210.
[29] Zhang, X., Zhou, B., Zeng, Y., and Gu, P., 2002, "Model
layout optimization for solid ground curing rapid prototyping
processes," Robotics and Computer-Integrated Manufacturing,
18(1), pp. 41-51.
[30] Hur, S.-M., Choi, K.-H., Lee, S.-H., and Chang, P.-K.,
2001, "Determination of fabricating orientation and packing in
SLS process," Journal of Materials Processing Technology,
112(2-3), pp. 236-243.
[31] Canellidis, V., Giannatsis, J., and Dedoussis, V., 2013,
"Efficient parts nesting schemes for improving
stereolithography utilization," Computer-Aided Design, 45(5),
pp. 875-886.
[32] Zhang, Y., Gupta, R. K., and Bernard, A., 2016, "Twodimensional placement optimization for multi-parts production
in additive manufacturing," Robotics and Computer-Integrated
Manufacturing, 38, pp. 102-117.
[33] Gogate, A., and Pande, S., 2008, "Intelligent layout
planning for rapid prototyping," International Journal of
Production Research, 46(20), pp. 5607-5631.
[34] Wu, S., Kay, M., King, R., Vila-Parrish, A., and Warsing,
D., "Multi-objective optimization of 3D packing problem in
additive manufacturing," Proc. IIE Annual Conference.
Proceedings, Institute of Industrial and Systems Engineers
(IISE), p. 1485.
[35] Pandey, P. M., Thrimurthulu, K., and Reddy, N. V., 2004,
"Optimal part deposition orientation in FDM by using a
multicriteria genetic algorithm," International Journal of
Production Research, 42(19), pp. 4069-4089.
[36] Thrimurthulu, K., Pandey, P. M., and Reddy, N. V., 2004,
"Optimum part deposition orientation in fused deposition
modeling," International Journal of Machine Tools and
Manufacture, 44(6), pp. 585-594.
[37] Phatak, A. M., and Pande, S. S., 2012, "Optimum part
orientation in rapid prototyping using genetic algorithm,"
Journal of manufacturing systems, 31(4), pp. 395-402.
[38] Huang, R., Ulu, E., Kara, L. B., and Whitefoot, K. S.,
"Cost Minimization in Metal Additive Manufacturing Using
Concurrent Structure and Process Optimization," Proc. ASME
2017 International Design Engineering Technical Conferences
and Computers and Information in Engineering Conference,
American Society of Mechanical Engineers, pp.
V02AT03A030-V002AT003A030.
[39] Johnson, M., and Kirchain, R., 2009, "Quantifying the
effects of parts consolidation and development costs on
material selection decisions: A process-based costing
approach," International Journal of Production Economics,
119(1), pp. 174-186.
[40] Rickenbacher, L., Spierings, A., and Wegener, K., 2013,
"An integrated cost-model for selective laser melting (SLM),"
Rapid Prototyping Journal, 19(3), pp. 208-214.
[41] Ulu, E., Huang, R., Kara, L. B., and Whitefoot, K. S.,
2018, "Concurrent Structure and Process Optimization for
Minimum Cost Metal Additive Manufacturing," Journal of
Mechanical Design.
[42] Baumers, M., Dickens, P., Tuck, C., and Hague, R., 2016,
"The cost of additive manufacturing: machine productivity,
economies of scale and technology-push," Technological
forecasting social change, 102, pp. 193-201.
[43] Dinda, S., Modi, D., Simpson, T. W., Tedia, S., and
Williams, C. B., "Expediting Build Time, Material, and Cost
Estimation for Material Extrusion Processes to Enable Mobile
Applications," Proc. ASME 2017 International Design
Engineering Technical Conferences and Computers and
Information in Engineering Conference, American Society of
Mechanical Engineers, pp. V02AT03A034-V002AT003A034.
[44] Ruffo, M., Tuck, C., and Hague, R., 2006, "Cost
estimation for rapid manufacturing-laser sintering production
for low to medium volumes," Proceedings of the Institution of
Mechanical Engineers, Part B: Journal of Engineering
Manufacture, 220(9), pp. 1417-1427.
[45] Yim, S., and Rosen, D., "Build time and cost models for
additive manufacturing process selection," Proc. ASME 2012
international design engineering technical conferences and
computers and information in engineering conference,
American Society of Mechanical Engineers, pp. 375-382.
[46] Ulu, E., Korkmaz, E., Yay, K., Ozdoganlar, O. B., and
Kara, L. B., 2015, "Enhancing the structural performance of
additively manufactured objects through build orientation
optimization," Journal of Mechanical Design, 137(11), p.
111410
[47] Gong, H., Rafi, K., Gu, H., Starr, T., and Stucker, B.,
2014, "Analysis of defect generation in Ti–6Al–4V parts made
using powder bed fusion additive manufacturing processes,"
Additive Manufacturing, 1, pp. 87-98.
[48] Murr, L. E., Gaytan, S. M., Ramirez, D. A., Martinez, E.,
Hernandez, J., Amato, K. N., Shindo, P. W., Medina, F. R.,
and Wicker, R. B., 2012, "Metal fabrication by additive
manufacturing using laser and electron beam melting
technologies," Journal of Materials Science and Technology,
28(1), pp. 1-14.
[49] Nie, Z., Wang, G., McGuffin-Cawley, J. D., Narayanan,
B., Zhang, S., Schwam, D., Kottman, M., and Rong, Y. K.,
2016, "Experimental Study and Modeling of H13 Steel Deposition Using Laser Hot-Wire Additive Manufacturing," Journal of Materials Processing Technology, 235, pp. 171-186.
[50] Toh, W. Q., Wang, P., Tan, X., Nai, M. L. S., Liu, E., and
Tor, S. B., 2016, "Microstructure and wear properties of
electron beam melted Ti-6Al-4V parts: A comparison study
against as-cast form," Metals, 6(11), p. 284.
[51] Inc., S., 2015, "Advantages of Wire AM vs. Powder AM," http://www.sciaky.com/additive-manufacturing/wiream-vs-powder-am.
[52] Gockel, J., Beuth, J., and Taminger, K., 2014, "Integrated control of solidification microstructure and melt pool dimensions in electron beam wire feed additive manufacturing of Ti-6Al-4V," Additive Manufacturing, 1-4, pp. 119-126.
[53] Chen, N., and Frank, M. C., "A method for metal AM support structure design to facilitate removal," Proc. Solid Freeform Fabrication, pp. 1516-1524.
[54] Vaidya, R., and Anand, S. J. P. M., 2016, "Optimum support structure generation for additive manufacturing using unit cell structures and support removal constraint," 5, pp.1043-1059.
Additive Manufacturing - Optimization of Part Consolidation for Minimum Production Costs and Production Time
Optimization of Part Consolidation for Minimum Production Costs and Time Using Additive Manufacturing
Zhenguo Nie, Sangjin Jung, Levent Burak Kara, Kate S. Whitefoot
Mechanical Engineering, Carnegie Mellon University
Engineering and Public Policy, Carnegie Mellon University
Pittsburgh, PA, USA
https://meche.engineering.cmu.edu/_files/images/research-groups/whitefoot-group/NJKW-OptPartConsolidation-JMD.pdf
Selected References
[1] Yang, S., Talekar, T., Sulthan, M. A., and Zhao, Y. F., 2017, "A Generic Sustainability Assessment Model towards Consolidated Parts Fabricated by Additive Manufacturing Process," Procedia manufacturing, 10, pp. 831-844.
[2] Yang, S., Tang, Y., and Zhao, Y. F., 2015, "A new part consolidation method to embrace the design freedom of additive manufacturing," Journal of Manufacturing Processes, 20, pp. 444-449.
[3] Yang, S., and Zhao, Y. F., 2015, "Additive manufacturing enabled design theory and methodology: a critical review," The International Journal of Advanced Manufacturing Technology, 80(1), pp. 327-342.
[7] Schmelzle, J., Kline, E. V., Dickman, C. J., Reutzel, E. W., Jones, G., and Simpson, T. W., 2015, "(Re) Designing for part consolidation: understanding the challenges of metal additive manufacturing," Journal of Mechanical Design, 137(11), p.111404.
[8] Frey, D., Palladino, J., Sullivan, J., and Atherton, M., 2007, "Part count and design of robust systems," Systems engineering, 10(3), pp. 203-221.
[9] Türk, D.-A., Kussmaul, R., Zogg, M., Klahn, C., Leutenecker-Twelsiek, B., and Meboldt, M., 2017,
"Composites part production with additive manufacturing technologies," Procedia CIRP, 66, pp. 306-311.
[10] Booker, J., Swift, K., and Brown, N., 2005, "Designing for assembly quality: strategies, guidelines and techniques," Journal of Engineering design, 16(3), pp. 279-295.
[11] Boothroyd, G., Dewhurst, P., and Knight, W. A., 2001, Product Design for Manufacture and Assembly, revised and expanded, CRC press.
[12] Combemale, C., Whitefoot, K. S., Ales, L., and Fuchs, E. R., 2018, "Not All Technological Change is Equal: Disentangling Labor Demand Effects of Automation and Parts Consolidation," Available at SSRN 3291686.
[13] Taufik, M., and Jain, P. K., 2013, "Role of build orientation in layered manufacturing: a review," International Journal of Manufacturing Technology and Management, 27(1-3), pp. 47-73.
[14] Jibin, Z., "Determination of optimal build orientation based on satisfactory degree theory for RPT," Proc. Computer Aided Design and Computer Graphics, 2005. Ninth International Conference on, IEEE, p. 6 pp.
[15] Thomas, D. S., and Gilbert, S. W., 2014, "Costs and cost effectiveness of additive manufacturing," Special Publication, NIST.
[16] Alexander, P., Allen, S., and Dutta, D., 1998, "Part orientation and build cost determination in layered manufacturing," Computer-Aided Design, 30(5), pp. 343-356.
[17] Langelaar, M., 2016, "Topology optimization of 3D selfsupporting structures for additive manufacturing," Additive Manufacturing, 12, pp. 60-70.
[18] Leary, M., Merli, L., Torti, F., Mazur, M., and Brandt, M., 2014, "Optimal topology for additive manufacture: a method for enabling additive manufacture of support-free optimal structures," Materials & Design, 63, pp. 678-690.
[19] Mirzendehdel, A. M., and Suresh, K., 2016, "Support
structure constrained topology optimization for additive
manufacturing," Computer-Aided Design, 81, pp. 1-13.
[20] Paul, R., and Anand, S., 2015, "Optimization of layered
manufacturing process for reducing form errors with minimal
support structures," Journal of Manufacturing Systems, 36, pp.
231-243.
[21] Vanek, J., Galicia, J. A. G., and Benes, B., "Clever
support: Efficient support structure generation for digital
fabrication," Proc. Computer graphics forum, Wiley Online
Library, pp. 117-125.
[22] Boothroyd, G., Dewhurst, P., and Knight, W. A., 2001,
Product Design for Manufacture and Assembly, CRC press.
[23] Yang, S., Santoro, F., and Zhao, Y. F., 2018, "Towards a
numerical approach of finding candidates for additive
manufacturing-enabled part consolidation," Journal of
mechanical design, 140(4), p. 041701.
[24] Chadha, C., Crowe, K., Carmen, C., and Patterson, A.,
2018, "Exploring an AM-enabled combination-of-functions
approach for modular product design," Designs, 2(4), p. 37.
[25] Yang, S., Santoro, F., Sulthan, M. A., and Zhao, Y. F.,
2019, "A numerical-based part consolidation candidate
detection approach with modularization considerations,"
Research in Engineering Design, 30(1), pp. 63-83.
[26] Nyaluke, A., Nasser, B., Leep, H. R., and Parsaei, H. R.,
1996, "Rapid prototyping work space optimization,"
Computers and industrial engineering, 31(1-2), pp. 103-106.
[27] Canellidis, V., Dedoussis, V., Mantzouratos, N., and
Sofianopoulou, S., 2006, "Pre-processing methodology for
optimizing stereolithography apparatus build performance,"
Computers in industry, 57(5), pp. 424-436.
[28] Wodziak, J. R., Fadel, G. M., and Kirschman, C., "A
genetic algorithm for optimizing multiple part placement to
reduce build time," Proc. Proceedings of the Fifth
International Conference on Rapid Prototyping, University of
Dayton Dayton, OH, pp. 201-210.
[29] Zhang, X., Zhou, B., Zeng, Y., and Gu, P., 2002, "Model
layout optimization for solid ground curing rapid prototyping
processes," Robotics and Computer-Integrated Manufacturing,
18(1), pp. 41-51.
[30] Hur, S.-M., Choi, K.-H., Lee, S.-H., and Chang, P.-K.,
2001, "Determination of fabricating orientation and packing in
SLS process," Journal of Materials Processing Technology,
112(2-3), pp. 236-243.
[31] Canellidis, V., Giannatsis, J., and Dedoussis, V., 2013,
"Efficient parts nesting schemes for improving
stereolithography utilization," Computer-Aided Design, 45(5),
pp. 875-886.
[32] Zhang, Y., Gupta, R. K., and Bernard, A., 2016, "Twodimensional placement optimization for multi-parts production
in additive manufacturing," Robotics and Computer-Integrated
Manufacturing, 38, pp. 102-117.
[33] Gogate, A., and Pande, S., 2008, "Intelligent layout
planning for rapid prototyping," International Journal of
Production Research, 46(20), pp. 5607-5631.
[34] Wu, S., Kay, M., King, R., Vila-Parrish, A., and Warsing,
D., "Multi-objective optimization of 3D packing problem in
additive manufacturing," Proc. IIE Annual Conference.
Proceedings, Institute of Industrial and Systems Engineers
(IISE), p. 1485.
[35] Pandey, P. M., Thrimurthulu, K., and Reddy, N. V., 2004,
"Optimal part deposition orientation in FDM by using a
multicriteria genetic algorithm," International Journal of
Production Research, 42(19), pp. 4069-4089.
[36] Thrimurthulu, K., Pandey, P. M., and Reddy, N. V., 2004,
"Optimum part deposition orientation in fused deposition
modeling," International Journal of Machine Tools and
Manufacture, 44(6), pp. 585-594.
[37] Phatak, A. M., and Pande, S. S., 2012, "Optimum part
orientation in rapid prototyping using genetic algorithm,"
Journal of manufacturing systems, 31(4), pp. 395-402.
[38] Huang, R., Ulu, E., Kara, L. B., and Whitefoot, K. S.,
"Cost Minimization in Metal Additive Manufacturing Using
Concurrent Structure and Process Optimization," Proc. ASME
2017 International Design Engineering Technical Conferences
and Computers and Information in Engineering Conference,
American Society of Mechanical Engineers, pp.
V02AT03A030-V002AT003A030.
[39] Johnson, M., and Kirchain, R., 2009, "Quantifying the
effects of parts consolidation and development costs on
material selection decisions: A process-based costing
approach," International Journal of Production Economics,
119(1), pp. 174-186.
[40] Rickenbacher, L., Spierings, A., and Wegener, K., 2013,
"An integrated cost-model for selective laser melting (SLM),"
Rapid Prototyping Journal, 19(3), pp. 208-214.
[41] Ulu, E., Huang, R., Kara, L. B., and Whitefoot, K. S.,
2018, "Concurrent Structure and Process Optimization for
Minimum Cost Metal Additive Manufacturing," Journal of
Mechanical Design.
[42] Baumers, M., Dickens, P., Tuck, C., and Hague, R., 2016,
"The cost of additive manufacturing: machine productivity,
economies of scale and technology-push," Technological
forecasting social change, 102, pp. 193-201.
[43] Dinda, S., Modi, D., Simpson, T. W., Tedia, S., and
Williams, C. B., "Expediting Build Time, Material, and Cost
Estimation for Material Extrusion Processes to Enable Mobile
Applications," Proc. ASME 2017 International Design
Engineering Technical Conferences and Computers and
Information in Engineering Conference, American Society of
Mechanical Engineers, pp. V02AT03A034-V002AT003A034.
[44] Ruffo, M., Tuck, C., and Hague, R., 2006, "Cost
estimation for rapid manufacturing-laser sintering production
for low to medium volumes," Proceedings of the Institution of
Mechanical Engineers, Part B: Journal of Engineering
Manufacture, 220(9), pp. 1417-1427.
[45] Yim, S., and Rosen, D., "Build time and cost models for
additive manufacturing process selection," Proc. ASME 2012
international design engineering technical conferences and
computers and information in engineering conference,
American Society of Mechanical Engineers, pp. 375-382.
[46] Ulu, E., Korkmaz, E., Yay, K., Ozdoganlar, O. B., and
Kara, L. B., 2015, "Enhancing the structural performance of
additively manufactured objects through build orientation
optimization," Journal of Mechanical Design, 137(11), p.
111410
[47] Gong, H., Rafi, K., Gu, H., Starr, T., and Stucker, B.,
2014, "Analysis of defect generation in Ti–6Al–4V parts made
using powder bed fusion additive manufacturing processes,"
Additive Manufacturing, 1, pp. 87-98.
[48] Murr, L. E., Gaytan, S. M., Ramirez, D. A., Martinez, E.,
Hernandez, J., Amato, K. N., Shindo, P. W., Medina, F. R.,
and Wicker, R. B., 2012, "Metal fabrication by additive
manufacturing using laser and electron beam melting
technologies," Journal of Materials Science and Technology,
28(1), pp. 1-14.
[49] Nie, Z., Wang, G., McGuffin-Cawley, J. D., Narayanan,
B., Zhang, S., Schwam, D., Kottman, M., and Rong, Y. K.,
2016, "Experimental Study and Modeling of H13 Steel
Deposition Using Laser Hot-Wire Additive Manufacturing,"
Journal of Materials Processing Technology, 235, pp. 171-
186.
[50] Toh, W. Q., Wang, P., Tan, X., Nai, M. L. S., Liu, E., and
Tor, S. B., 2016, "Microstructure and wear properties of
electron beam melted Ti-6Al-4V parts: A comparison study
against as-cast form," Metals, 6(11), p. 284.
[51] Inc., S., 2015, "Advantages of Wire AM vs. Powder
AM," http://www.sciaky.com/additive-manufacturing/wiream-vs-powder-am.
[52] Gockel, J., Beuth, J., and Taminger, K., 2014, "Integrated
control of solidification microstructure and melt pool
dimensions in electron beam wire feed additive manufacturing
of Ti-6Al-4V," Additive Manufacturing, 1-4, pp. 119-126.
[53] Chen, N., and Frank, M. C., "A method for metal AM
support structure design to facilitate removal," Proc. Solid
Freeform Fabrication, pp. 1516-1524.
[54] Vaidya, R., and Anand, S. J. P. M., 2016, "Optimum
support structure generation for additive manufacturing using
unit cell structures and support removal constraint," 5, pp.
1043-1059.
[55] Jebari, K., and Madiafi, M., 2013, "Selection methods for
genetic algorithms," International Journal of Emerging
Sciences, 3(4), pp. 333-344.
[56] Inc., S., 2016, "EBAM 300 Series,"
https://www.aniwaa.com/product/3d-printers/sciaky-ebam300-series/.
Design To Value - Design For Value (DTV) - Procedure and Case Studies
Design-to-value - McKinsey's View
Design-to-value (DTV) is an integrated approach to product development that considers multiple perspectives:
What customers want?
What competitors are offering?
What it costs to manufacture and distribute an end product?
As a part of DTV, companies interact with customers and identify the product features that consumers value most, as well as those that generate little market interest. Based on this information, they can redesign their products, adding new features that promote sales while eliminating unnecessary attributes. DTV also evaluates cost elements of products and helps companies optimize efficiency in product design and manufacture by highlighting areas for improvement.
DTV is in application in many companies. The applications are available across multiple industries, including automotive and assembly, high tech, telecom, consumer goods, and electronics.
DTV is a systematic, fact-based approach
During the DTV process, all product development decisions are based on facts— hard data from consumer research, clean-sheet-based cost models, and competitive intelligence from teardowns of products of competitors.
Developing a robust and deep understanding of features that drive value up and quantifying their how much consumers are willing to pay for those product features highlights important product features that need to be added. Conducting “teardowns” of competitors' products to document technical and functional differences provide ideas for reducing costs of providing various features,
Clean sheet modeling, which involves determining the detailed “should cost” for each product and developing strategies to reduce expenses based on that "should cost", by redesigning products or processes or by negotiating differently with suppliers
After doing the three information gathering steps and developing various ideas by involving many experts from various functions, the list of ideas is compiled for further evaluation. In the evaluation process, a list of specific and pragmatic ideas that companies can implement to increase customer value while reducing product costs is arrived at.
By using the DTV methodology, many companies have redesigned and optimized their products and uncovered significant savings—often in unexpected areas.
Across sectors, DTV stimulates growth, improves customer satisfaction, and optimizes brand positioning by keeping the focus on product features that customers value. This results in impressive financial benefits. McKinsey claims that on average, our clients achieved a 10 to 40 percent increase in gross margin and a 10 to 40 percent reduction in product and supply chain cost. DTV also helps increse product preference in the market and helps companies gain additional market share as well.
DTV Resources and Capabilities of McKinsey
McKinsey has invested significant time and resources into DTV over the last decade, and now has many proprietary, cutting-edge assets to assist clients. These include:
A database of 400 should cost sheets that show labor rates, material costs, and machine costs are created by them.
A library of linear performance pricing models to help clients identify when the cost of commodities and standard parts, such as batteries, motors, or raw materials, appears to be excessive
Proprietary software that allows clients to track and manage their innovative product improvement ideas from creation to implementation and financial validation.
It has a pool of over 300 experts and consultants who are trained in DTV techniques, many of whom have deep technical knowledge and several years of industry experience in relevant fields. They lead and facilitate workshops for cross-functional client teams composed of a general manager and staff from marketing, engineering, operations, and other groups.
McKinsey holds workshops at client sites or in one of their global design labs. They can create design labs in client organizations also.
http://www.mckinsey.com/business-functions/operations/how-we-help-clients/product-development/design-to-value
McKinsey Case Studies
Redesign of Medical Device
http://www.mckinsey.com/business-functions/operations/how-we-help-clients/break-down-silos
DTV Application to Forklift Truck
http://www.mckinsey.com/business-functions/operations/how-we-help-clients/redesign-equipment-for-lower-costs
DTV Application to Household Fan
http://www.mckinsey.com/business-functions/operations/how-we-help-clients/redesign-to-innovate-compete
Teardown Value Analysis
The teardown showed that as compared with competitors, the company was “overbuilding” its products significantly and that identical—or even better—product performance was possible at a lower cost if the team was willing to rethink its design approaches (VE opportunity identified).
DTV Applied to Shampoo Packaging
http://www.mckinsey.com/business-functions/operations/how-we-help-clients/reduce-packaging-costs
Designing Products for Value - McKinsey Quarterly
By Ananth Narayanan, Asutosh Padhi, and Jim WilliamsMcKinsey Quarterly October 2012
http://www.mckinsey.com/business-functions/operations/our-insights/designing-products-for-value
2023
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Design-to-value - BCG's View
The environment of low growth and rapid product life cycles, requires from companies products and services that provide the greatest total value to customers (thus get the highest price) and the most attractive economics (profit margins) over the life cycle of the product. Design to value (DTV) is a cross-functional product development and improvement process that achieves these dual objectives by translating top-level strategy (product - market choice) into design choices for products and services as well as the underlying processes in the production facilities of the company and the facilities of the supply chain partners. DTV allows companies to focus their innovation (creation and commercialization) efforts on the features that their customers are willing to pay for and to select cost optimization approaches that will improve and protect long-term profitability.
Boston Consulting Group's Capabilities in DTV
The Boston Consulting Group has developed a flexible and broadly applicable approach to DTV that companies in diverse industries can apply to both new and existing products and services. The approach uses “catalyst events”—workshop sessions in which a team of cross-functional executives, operators and stakeholders apply a robust fact base to generate ideas for designing the best products with minimal complexity and cost. The executives and operators are from engineering, production, procurement, and sales and marketing for these events. This team effort breaks down organizational silos and increasing agreement on strategic priorities across business functions due to information transfer that takes during discussions. Some companies also involve their customers or suppliers in these workshops.
https://www.bcgperspectives.com/content/articles/sourcing-procurement-operations-design-value-advantage/
Design To Value - PWC
http://www.strategyand.pwc.com/media/file/Strategic-product-value-management.pdfCompanies require a unique set of capabilities — which PWC refers to as strategic product value management — to reduce product costs, drive growth, and expand margins. Strategic product value management uses commercial and design levers to provide the discipline and methodology required to manage the product development. It adds significant value early in the process, particularly through two aspects: design to value (DTV) and design to cost (DTC). Design to value entails analyzing what customers need in terms of features, efficacy, or other attributes (i.e., the value proposition of a particular product, including pricing). Design to cost, by contrast, entails analyzing all costs of a particular product and developing rigorous models to reduce those costs at every
possible juncture.
Design To Cost - Capgemini
https://www.fr.capgemini-consulting.com/resource-file-access/resource/pdf/design_to_cost.pdfOptimize Cost Across Value Chain and Product Lifecycle
https://www.cognizant.com/whitepapers/optimizing-product-realization-costs-across-the-value-chain-codex1611.pdfDesign To Value - Other Consultants
http://www.hillerassociates.com/design-to-value-versus-design-to-cost-versus-minimum-viable-product/
http://www.schoeler.com/en/web/mission-and-activities.php?kapitel=1
Design to Value – A cost reduction study of a specific wastewater pump
Thesis submitted for examination for the degree of Master of Science in Technology11.1.2016
https://aaltodoc.aalto.fi/bitstream/handle/123456789/19923/master_Mangs_Valter_Mangs_2016.pdf?sequence=1
Techniques involved in Design To Value Method
Should Cost Modeling
https://www.quest-global.com/wp-content/uploads/2015/07/Should-Cost-Challenges-Demystified-A-must-read-for-effective-cost-management-in-organizations.pdf
Management of Design To Value Programme
http://nraoiekc.blogspot.com/2016/10/management-of-design-to-value-programme.htmlI came to know of this method through a presentation a J & J team on 21 October 2016
Director, Design-to-Value – MRI
Director of DTV (Design-to-Value) / Value Engineering
Johnson & Johnson, Bridgewater, NJAdvertisement in October 2016
Job Description
Johnson & Johnson Family of Companies is currently recruiting for a Director of DtV (Design-to-Value) / Value Engineering. This position can be located in Bridgewater, NJ, USA or Zug, Switzerland.
Caring for the world, one person at a time, inspires and unites the people of Johnson & Johnson. We embrace research and science bringing innovative ideas, products and services to advance the health and well-being of people. Employees of the Johnson & Johnson Family of Companies work with partners in health care to touch the lives of over a billion people every day, throughout the world.
The Director DtV / Value Engineering will:
• Lead or Co-Lead DtV product conventions and other DtV project types
• Role-model DtV behavior and cross-functional ways of working
• Create positive financial impact with DtV savings and value creation opportunities
• Follow-up at high level on convention results and selectively further guide or assist segment staff responsible for implementation
• Assist businesses and partner with R&D and commercial in identifying and assessing opportunities and planning a DtV roadmap, with the objective of creating and maintaining a continuous stream of DtV work
• Create showcases on DtV application and further develop our process descriptions and training materials
• Assist in developing the Design-to-Value (DtV) Process and Framework, as an integrated approach to Product Development considering multiple dimensions: Customer, Quality, Cost, Technology, Value Add
• Ensure that the DtV processes are properly documented, provide work instructions which have to be used by the operational/segment teams, indicating in particular the intersection points between the functions with clear R&R; important in the cross functional supply chain environment.
• Be aware of product related trade-offs and make best use of the customer / consumer insights, to ensure DtV improves overall product competitiveness, with proper balance of cost and attractiveness while ensuring quality and regulatory compliance
• Identify and drive leverage DtV opportunities wherever reasonable. Across business, or across segment. Use / integrate centrally managed resources as well, wherever appropriate
Qualifications
• University degree in engineering or scientific field is required, an advanced scientific degree (MS) or MBA is preferred
• Minimum of 10 years of experience in engineering / R&D, manufacturing, product management or supply chain (ideally across multiple functions) is required, as well as broad technical and scientific expertise
• Expertise in understanding Product Development and Design is required
• Understanding the linkages from product development through manufacturing and delivery to the customer is required, deep practical understanding of the linkage between product and process development is required
• Leadership experience in a large scale multi-location operational change program, preferrably DtV / Value Engineering, but possibly also Six Sigma or Lean programs is preferred
• Familiarity with state-of-the art DtV tools, including consumer / marketing related tools is preferred
• Multifunctional background, or proven track record of working easily and achieving results across functional boundaries is required
• Understanding of typical regulatory and quality requirements is preferred
• Ability to create strong relationships across multiple functions and businesses is preferred
• Change management and project management experience is required
• Strong executive presentation skills is required
• Strong analytical and strategic skills with a Bifocal approach - ability to zoom-in/zoom-out for strategic and tactical, high-level and detailed, etc. is required
• Experience in driving broadly based culture change in a train-the-trainer setting is required
2020 Job Notification
Design to Value Manager - Product Supply
Consumer Products Industry Company SC Johnson, Racine, WI, United StatesJOB DETAILS – THIS JOB HAS EXPIRED,
Job Description
Position Purpose:
DTV Manager responsible for cost savings discovery and execution. Overall Program Lead or Product Supply Lead on various teardowns. Project Manager or Product Supply Lead for execution of global cost savings initiatives.
Primary Accountabilities:
Provide overall leadership and in-depth knowledge of Supply Chain, Procurement, and Manufacturing in the DTV Teardown process.
Lead and or participate in Teardowns globally to evaluate and assess opportunity in the entire supply chain including suppliers, manufacturing locations and distribution networks.
Work with the team and external partners to convert learning and insights into meaningful actions. Provide perspectives on insights & potential manufacturing impacts, identifying key information gaps, and providing leadership in the development and execution of initial concepts as they relate to consumer value and cost savings.
Collaborate to revise the Teardown Playbook to reflect process improvements throughout the year.
Serve as Project Manager or Product Supply Lead for execution of DTV & Procurement cost savings initiatives.
Work with cross functional partners to define project scope and success criteria.
Develop and maintain project plans and budgets while ensuring project milestones are met.
Provide consistent two way communication between project teams and management.
Ensure alignment with Senior Leadership through regular milestone updates.
Experience/Skills/Knowledge
Independently, and working with others, able to generate new, innovative ideas and related technologies to improve consumer value and reduce costs.
Experience leading cross functional projects against demanding timelines. Microsoft Project experience required.
Demonstrated sense of urgency and decisiveness; takes prompt action to accomplish goals; proactively attempts to influence events rather than passively accept outcomes.
Demonstrated high level of curiosity, creativity, and strong problem solving skills.
Able and willing to transition quickly to different tasks, to shift priorities and modify actions to meet changing job demands at short notice.
Ability to effectively communicate new ideas to audiences ranging from team members to Senior Leadership
Experience working with a global team.
The ideal candidate will have knowledge of multiple areas of Product Supply including production and processing equipment, manufacturing technologies and supply chain.
Competencies
Team Leadership and Development
Strategic Partnership
Supplier Relationship Management
Negotiations and Financial Analysis
Performance Analysis and Improvement
Risk & Opportunity Management
Project Management
Influencing
Qualifications
BS degree in Engineering, Supply Chain, Business, or related field
Minimum of 7 years of Project management experience
Strong knowledge of production processes/technologies like Lean, Six Sigma, Kaizen, OEE, TPM
Proficient computer skills including Word, Excel and PowerPoint, MS Project.
Strong interpersonal and presentation skills
MBA preferred.
https://www.velvetjobs.com/job-posting/design-to-value-manager-product-supply-p14171422
Updated on 26.11.2023, 13 March 2020, 21 October 2016
Product Industrial Engineering Section - Value Engineering Section - Effective Organization
Performance orientation, focus on the specified performance of engineering products, machines and equipment and even factories, received the maximum emphasis in american engineering organizations for many many years as customers will not buy a product that does not perform. But the cost aspect did not receive the adequate attention despite the effort of American Society of Mechanical Engineering since its founding. F.W. Taylor made significant contribution to cost reduction through productivity improvement of resources, machines and men. He advocated that science of working of machines and men is to be developed and productivity science developed in that endeavor will increase production from the same machine and man and will give lower cost of production and higher wages to workmen. He explained his experiments, theory and the systems implemented by him in four important publications (System for increasing productivity - Elementary Rate Fixing Department (Piece Rates 1895), Shop Management (1903), The Art of Metal Cutting (1907) and Scientific Management (1911)).
L.D. Miles in his 1961 book reiterates the same. The company managements have not given adequate attention to managing costs despite the promotion of the idea efficiency counsel by Harrington Emerson his 12 principles of efficiency. Value engineers are specially trained men in value work using an appropriate set of techniques and management has to employ them and provide their internal consulting to all decision makers related to the products. It is not that all engineers and managers should not be given basic value engineering education and they have to be encouraged to take rational value and cost decisions. But specialist value engineers are required to maximize the value of value analysis and engineering methods available for implementation.
In 1961, Miles wrote that in businesses below $200,000 per year, the owner should get himself trained in value analysis and engineering. In businesses of $200,000 to $2 million, one among the top three needs to be trained in value engineering.
In businesses with sales of more than $2 million, one value engineer can be appointed. Before appointment, the management has adequate understanding and even practice of value engineering in the previous years. Real attention to the newly appointed value engineer and his functioning has to be given by the management till his work is accepted by every phase of the business especially engineering, manufacturing and purchasing.
Value Engineering Department
Three Skills of Value Engineering: Value engineering requires skill in engineering ideas (design of mechanisms and machine elements), in manufacturing methods and processes, and in the very extensive field of using vendor and specialty-vendor competence.
When two value engineers are working, both must act as independent internal consultants to specific decision makers and they both have to act as consultants to each other. One of them may be senior and has oversight responsibility for the other. But still, it is not assistant relationship. Both are independent and must have independent projects.
Miles said, three men constitute the smallest efficient operating unit for value work. Each consultant may have a special depth in one of the three value analysis and engineering skills. This will ensure that in each value project, each of the skills is fully utilized. But still each consultant needs to have independent projects and he can take the consultancy support from the other two value engineering team members.
In the case of four member team, one may have management responsibility for the whole team.
Ud. 26.11.2023
Pub. 15.11.2023