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CADDZOOMYour CAD / CAM Highway

SEPTEMBER 2019 | VOLUME - 15 | ISSUE - 06

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IN T

HIS IS

SUE

Skills Driven. Job Led

Trends influencingManufacturing Technology

PAGE 02

Inviting article and blog writers for CADDZOOM

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Electrical and mechanicalDesign Collaboration -4 Rules

PAGE 03

The Engineering and Construction Industry is one of the fastest and most lucrative industries in the world. Due to its massiveness, it is now on its way to join hands with digital technology, Artificial Intelligence, and Machine Learning. These initiatives aim to meet the growing demands of more and more buildings soon.

The Annual Connect and Construct Summit conducted in London recently by Autodesk discussed how the construc�on industry could tackle this growing demand. One of the construc�on partners at the event was the Royal BAM Group. It is a lifecycle construc�on firm with several projects all over the world. These firms use the concepts of Machine Learning to enhance their workflow. There are several other reasons why these companies are using Machine Learning to power their business;

Data Analysis

The concepts and methods of Machine Learning can collect a massive amount of construc�on data. These tools can then use this data to catch errors and fixing them in a short �me. The concept also helps to saves costs in hiring experts and fixing errors.

Insights by Construc�on IQ

Construc�on IQ is a part of Autodesk 360 pla�orm which uses BIM project data and machine learning to predict risks associated with a project. The technology is also able to iden�fy some issues which were difficult to predict otherwise such as fall hazards, water hazards, pending inspec�ons, and even issue which is overdue from a long �me.

Machine learning tools can categorize these issues into high and low risks and no�fy the contractors and subcontractors about them. Construc�on IQ also iden�fied one of the biggest risks that focused on the human errors. It was found that workers at several �mes fix the issue indicated by the system manually but forget to close it in the system. This revealed the digital shortcomings of the present systems and the areas on which machine learning needs interven�on. The machine learning algorithms thus helped the

construc�on professionals by providing realis�c insights with the help of smart algorithms to mi�gate them.

Empowering BIM 360

Machine learning-powered Construc�on IQ, together with BIM 360 helped the construc�on teams to reveal ac�onable details and improved performance. For instance, it increased number of ac�ve users in BIM 360 tool, increased number of ac�ve projects in BIM 360, the BIM Collabora�on tool also saw addi�onal ac�ve projects in BIM 360 Glue, and the BIM construc�on Docs also saw a surge in ac�ve users.

Overall, the concept of machine learning and automation are gaining more success today than ever before. Apart from the other domains, it is also on its ways to revolutionize the construction industry. The technology will also help to develop innovative and stronger building designs in the near future.

HOWMACHINE LEARNINGHOWMACHINE LEARNINGIS IMPROVINGCONSTRUCTION

CADDZOOM | SEPTEMBER 2019Skills Driven. Job Led

Manufacturing is often seen as producing physical things, transferring them to another and so forth. However, the scenario is no more the same. Ever-changing demand for quick delivery, customized products, market engagement; along with increase in economic production as well as the shift in supply chain have brought change in the way manufacturing businesses operate.

Therefore, organiza�ons are required to incorporate cost-effec�ve techniques while doing business in order to become produc�ve. Increased efficiency, enhanced awareness, decrease in the requirement of breaks and down�me, improvement in the quality of products, etc. are a reflec�on of some recent developments in manufacturing technology.

Increased efficiency is the end goal of manufacturers as it helps in energy consump�on, where technology plays a major role in saving power.

Improvement in product quality can help in elimina�ng the errors in the making of same products when the ul�mate aim is consistency. Quality concerns, securing the reputa�on of the business as well as the ability to meet the ever-changing demands, can deal with enhancing product quality.

A decrease in the requirement of breaks and down�me can constantly help with produc�on delays.

Greater awareness can be explained in terms of monitoring the working state of every delicate part of the business, star�ng from order number to product sta�s�cs.

Some other areas of trends having an influence on the manufacturing technology are highlighted below.

ARTIFICIAL INTELLIGENCE

The future is all good with AI integrated technology in the manufacturing world. The AI market is es�mated to grow from $8billion to $72 billion between 2016 and 2021. AI helps manufacturers to op�mize the use of equipment, enhance workflow efficiency,

improve recruitment process, and op�mize predic�ve analy�cs.

The branches of AI in the manufacturing sector involves:

Computer vision

Robo�cs

Automated planning and scheduling

Natural language processing

Speech recogni�on

3D PRINTING MAKING ITS WAY

“The line between supply chain and manufacturing are becoming difficult to dis�nguish,” says Lou Rassey, CEO of Fast

Radius (an addi�ve manufacturer based in Chicago). He further adds that the things we produce have the power to change the ways we live, making it simple. Addi�ve manufacturing helps in ge�ng new and powerful tools that bring picture into reality, which was once a mere imagina�on.

It has been predicted that prin�ng of aerospace, defence parts as well as automo�ve designs will be the biggest manufacturing sectors to employ 3D prin�ng.

The fastest-growing sectors involve:

Prototype prin�ng

Medical implant or device prin�ng

Dental prin�ng

Product crea�on

THE FUTURE OF MANUFACTURING TECHNOLOGY AND PROCESSES Looking forward to the growing opportuni�es which the manufacturers must grab, it is important to pay a�en�on to the technology essen�al for their current and future needs. It has to be a priority to profit from emerging technologies such as AI, as well as 3D prin�ng, along with listening to customer demand and capitalizing on R&D.

TRENDS INFLUENCINGMANUFACTURING

Image courtesy: https://blog.grabcad.com | https://www.engineering.com | https://meritsolutions.com | www.javelin-tech.com | https://aecscene.com |

CADDZOOM | SEPTEMBER 2019Skills Driven. Job Led

evelopment of intricate and convergent designs is a fact CAD software is starting to live with. The adoption is happening in many ways; one of the prominent ways is the collaboration of electrical and mechanical design. Products now need better integration for better mechanical stability, electrical components, and unified industrial design. Due to the same, the barrier between electrical and mechanical designers is worn down.

How can electrical and mechanical teams work collabora�vely, is that even a good idea? Let us discuss some rules to take the design team on the right path.

RULE 1 – Communica�on within Design Teams with Universally Shared Data

Data silos take place when the electrical and mechanical designers are unable to share data effec�vely. To enhance collabora�on:

Breaking these data silos completely can be a be�er approach. While following this approach, both the electrical and mechanical teams must be able to access the same universal data.

The real-�me, as well as up-to-date version of the PCB, should be seen by the mechanical designer for his designing enclosure.

Conflict of components with mechanical design change must be immediately seen by the electrical engineer.

RULE 2 – Close the Gap between ECAD and MCAD

It will be much be�er to access the data in a way that is appropriate for both design teams.

No need for other so�ware to access data for both electrical and mechanical teams.

It is cri�cal for design so�ware to adjus�ng and house mul�disciplinary teamwork.

Making data accessible for each team in a way they both can work together and implement a bidirec�onal workflow.

An MCAD perspec�ve is presented here as SOLIDWORKS, and

ECAD perspec�ve is presented as Al�um Designer; however both presented with varied perspec�ve eventually showing same data.

RULE 3 – Compa�ble Digital Tools across Engineering Disciples

Bidirec�onal flow of data all over the designing so�ware can turn out as the best way to start.

ECAD and MCAD tools must establish a consistent design se�ng. Collabora�ve features such as revision history as well as comments, can be accessed from any applica�on.

The issues of data silos and ineffec�ve communica�on techniques will flourish unless the applica�on is not compa�ble.

Rule 4 – Reduce Data Transi�on Overhead and Maximize Results

When more than one applica�on, namely ECAD and MCAD is used by a design team which was not designed for data interoperability, the it is unavoidable to use data transla�on program.

Success or failure of data transla�on is based on the model’s complexity as well as the data formats in the ques�on.

Data transla�on is sheer overhead that does not add any value to a product designing team.

Designers can effec�vely use their �me by removing the need for workflow and quickly launch their product to the market.

Nevertheless, if the software used by you is not as interoperable as defined in the above four rules, find a way to abate data translation to develop collaborative success with electromechanical design teams.

D

4 RULES FOR BETTERELECTRICAL AND MECHANICALDESIGN COLLABORATION