Posts tagged as:

Engineering

future-engineering-ref-books

I remember one of my birthdays back many years ago. My dad pushed me towards a bookshelf with kids encyclopedia and encourage me to study most of it for the next year. I found reference to these books on wikipedia now.  According to the information on wikipedia, it contained only ~6000-10000 pages. It was huge amount of information back that days. Also, I remember my first introduction into library of engineering codes and standards. I remember first day I had an access to Encyclopedia Britannica. The old way accessing information…

Everything changed since then. We are not looking for books when we need to get an information about anything. We “google it”… The voice recognition technologies is getting better, so since last month I can try to ask my Android wear device for information. It doesn’t work for everything, but it is getting better.

The fundamental change happened with encyclopedia business. It  became completely horizontal. Time ago a small team of people worked to create an encyclopedia that was consumed by millions of people for a long time. Now it is different – wikipedia changed the way we create knowledge and consume knowledge. The knowledge is crowdsourced by millions of people and consumed at the same time.

digital-revolution-phases-encyclopedia

The way we present knowledge is also changed. Reference books with plain text pages are thing in the past. Today, knowledge represented as a intertwined linked data set with references and rich media – videos, photos, maps and even 3D reconstructed objects. Here is an interesting example of how 3D and information technology can change museum business – Smithsonian X 3d.

New technologies in the field of knowledge capturing and representation combined with new approaches in data management and 3D scanning can change the way we work with information. I’ve been reading Kalypso article – Reference Books and Libraries – So “Yesterday”, which speaks exactly about that:

Let’s face it; libraries, reference books and dictionaries are losing their luster. Exploration and learning today are more likely done through online resources like Google, online research and scholarly journals, Wikis and blogs. So what does this mean for innovation and product development research processes?

Today, three ring binders and file cabinets still clutter the offices of marketers and market researchers at Fortune 500 companies that are considered leaders in innovation. Most of these companies probably have sophisticated enterprise information systems that contain sales information, financials, product data records, inventory and even employee time‐tracking.

Surprisingly, these companies may still track their historical ideation, concept, and project information in three ring binders or manila folders stacked in closets or stored in the basements of a research facility.

Earlier this week I learned about interesting project – LODLAM (Linked Open Data in Libraries Archives and Museums). If you have few minutes free, navigate to that website and take a look. It also brought me back to the ideas of usefulness of Knowledge Graph for PLM. I found a very good capture of current status of how LODLAM approach used to develop new type of information application is the presentation from SemTechBiz 2014. Take a look on the slides here.

lodlam-example

All together, it made me think about engineering standards and reference books. It is so old and not efficient. In many cases, engineers are relying on memories because access to the libraries, codes and information is too complicated. Like encyclopedia Britannica existing engineering references look are outdated and complicated to use.

The more I thought about that, more questions came to my mind. How to find relevant engineering codes and standards online? The diversity of engineering disciplines is very high. There are lots of specific industry oriented codes as well as country specific standards and references. How large companies are working with that? Who is curating this information for large industry leaders as well as for millions of small manufacturers and individual makers.

What is my conclusion? The way engineering standards and references are represented today is outdated. The best engineering libraries I found on the web are bunch of university libraries. The data is poorly organized and search mechanism  is far from perfect. How to organize engineering references and provide a better access to engineers. Do you think software vendors looking for that? Will future engineering information and design systems provide an access to reference information as part of design and manufacturing processes? Too many questions today :) . I have some answers, but I’m looking for some crowdinformation today. Just my thoughts…

Best, Oleg

Share

0 comments

historical-part-numbers

Part Numbers is a fascinating topic. I’m coming back to blog about what is the best approach to manage Part Numbers. My last post about it was – Part Numbers are hard. How to think about data first? was just few weeks ago. In that article, I outlined few principles how to keep PN separate from surrounding data focusing on different aspects of parts – description, classification, configurations, suppliers, etc.

Yesterday, my attention  was caught by ThomasNet article – Are Part Numbers Too Smart for Their Own Good? The article nailed down a key issue why companies are still having difficulties with management of Part Numbers. Nothing works from scratch in engineering companies. Complexity of characteristics and history of existing Part Numbers and products are making real difficulties to adopt new PN management concepts. The following passage explains the problem:

Another problem with descriptive numbering is that the description can become out of date and irrelevant over time. Individual parts can have their own life cycles; if a part has been identified according to the product, what happens if that product is discontinued but the part continues to be used in a newer product? Or what if a manufacturer changes vendors and the part number contains the name of the vendor that originally provided the piece?

Gilhooley admits that some Ultra Consultants clients have decided that switching from descriptive to auto-generated numbering would require too much organizational change. Some companies stick with old systems, and some opt for hybrid systems that perhaps retain descriptive numbers for existing parts but use auto-generated numbers for new parts.

It looks like there is no single solution or best practice to solve the problem. The “traditional” engineering approach to keep options to manage a diverse set company configuration looks like the only possible way to solve this problem in existing PLM/ERP systems.

What is my conclusion? History keeps customers from moving forward. There are two aspects of complexity in Part Numbers: 1/ complexity of definition and data classification; 2/ historical records of PN in every company including catalogs and existing products. Together, they create a block to make any changes in existing PN schema and prevent companies from migration towards new approaches. New data modeling technologies must be invented to handle existing data as well as supporting customers to migrate into modern PLM and ERP solutions. Just my thoughts…

Best, Oleg

Share

10 comments

google-data-center-crunches-engineering-data

The scale and complexity of the data is growing tremendously these days. If you go back 20 years, the challenge for PDM / PLM companies was how to manage revisions CAD files. Now we have much more data coming into engineering department. Data about simulations and analysis, information about supply chain, online catalog parts and lot of other things. Product requirements are transformed from simple word file into complex data with information about customers and their needs. Companies are starting to capture information about how customers are using products. Sensors and other monitoring systems are everywhere. The ability to monitor products in real life creates additional opportunities – how to fix problems and optimize design and manufacturing.

Here is the problem… Despite strong trend towards cheaper computing resources, when it comes to the need to apply brute computing force, it still doesn’t come for free. Services like Amazon S3 are relatively cheap. However, if we you want to crunch and make analysis and/or processing of large sets of data, you will need to pay. Another aspect is related to performance. People are expecting software to work at a speed of user thinking process. Imagine, you want to produce design alternatives for your future product. In many situations, to wait few hours won’t be acceptable. It will be destructing users and they won’t use such system after all.

Manufacturing leadership article Google’s Big Data IoT Play For Manufacturing speaks exactly about that. What if the power of web giants like Google can be used to process engineering and manufacturing data. I found explanation provided by Tom Howe, Google’s senior enterprise consultant for manufacturing quite interesting. Here is the passage explaining Google’s approach.

Google’s approach, said Howe, is to focus on three key enabling platforms for the future: 1/ Cloud networks that are global, scalable and pervasive; 2/ Analytics and collection tools that allow companies to get answers to big data questions in 10 minutes, not 10 days; 3/ And a team of experts that understands what questions to ask and how to extract meaningful results from a deluge of data. At Google, he explained, there are analytics teams assigned to every functional area of the company. “There’s no such thing as a gut decision at Google,” said Howe.

It sounds to me like viable approach. However, it made me think about what will make Google and similar computing power holders to sell it to enterprise companies. Google ‘s biggest value is not to selling computing resources. Google business is selling ads… based on data. My hunch there are two potential reasons for Google to support manufacturing data inititatives – potential to develop Google platform for manufacturing apps and value of data. The first one is straightforward – Google wants more companies in their eco-system. I found the second one more interesting. What if manufacturing companies and Google will find a way to get an insight from engineering data useful for their business? Or even more – improving their core business.

What is my conclusion? I’m sure in the future data will become the next oil. The value of getting access to the data can be huge. The challenge to get that access is significant. Companies won’t allow Google as well as PLM companies simply use the data. Companies are very concerned about IP protection and security. To balance between accessing data, providing value proposition and gleaning insight and additional information from data can be an interesting play. For all parties involved… Just my thoughts..

Best, Oleg

Share

0 comments

PLM, ERP and the death of over the wall engineering

July 31, 2014

Do you remember “throw over the wall of manufacturing” statement? This is a traditional engineering world. Pretty much sequential. Engineers are doing their job and throw it over the wall to the next stage. Traditional manufacturing was driven by sales forecast. This is was the world that formed a traditional domains of PDM/PLM and ERP. […]

Share
Read the full article →

Why cloud engineering collaboration tools are slow to ramp up

July 15, 2014

Few weeks ago I attended Boston Tech Jam and learn new buzzword – YAPSA. Which stands for Yet Another Photo Sharing Application. The amount of cloud files and data sharing applications is skyrocketing these days. It inspired many developers to re-think how to share and collaborate with engineering data.  Cloud technologies made people to bring back […]

Share
Read the full article →

PLM and 25 years of Internet

March 13, 2014

It has been 25 years of Internet anniversary yesterday. Lots of article covering this event were flown around earlier this week. The Independent article – 25 years of the World Wide Web: Tim Berners-Lee explains how it all began covers the story together with world wide web inventor Tim Berners-Lee. Even we all know about how […]

Share
Read the full article →

PLM, Social and Fake Incentives

September 14, 2013

Social hype is over. Period. I hope, I’ve got a social attention now . Despite that conclusion, social topic keeps me busy on the blog. A year ago I posted How to prevent social PLM from marketing fluff. My observation in that post came from watching multiple “Facebook clones” everywhere.  Few weeks ago I posted […]

Share
Read the full article →

GrabCAD and Open Engineering Source: Dream or Reality?

September 8, 2013

Everybody knows about open source software (OSS). The model of OSS skyrocketed for the last decade and made lots projects on the web very successful. The evolution of open source wasn’t simple. It evolved from just making software source code available to quite complicated system of open software licensing. Open source inspired lots of new initiatives. One […]

Share
Read the full article →

PDM 101: Engineering Document Management Fallacy

August 30, 2013

We love new technologies and trends. However, from time to time, I want to get back to basic topics of engineering and manufacturing software. The topic I’d like to discuss today is Engineering Document Management (EDM). This post was triggered by DM vs. EDM article by Scott Cleveland on 2PLM letter. Here is the passage Scott […]

Share
Read the full article →

BOM 101: How to optimize Bill of Materials

January 14, 2013

Last week, I started the conversation about Bill of Materials and modern challenges. BOM is a heavy topic. Previous blog made me think about few additional things related to BOM management and I decided to share it with you too. One of the concepts I see as important in modern PLM and other enterprise systems […]

Share
Read the full article →