A New Model for Manufacturing Innovation

By Valerie C.
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by Werner Krings

The Austrian Economist Joseph Schumpeter argued that industries must incessantly revolutionize their economic structure from within. I interpret this statement to mean that manufacturers, especially in the High Tech industry, must continually strive to innovate with better or more effective processes in order to build new products.

Innovation is a core attribute of successful High Tech manufacturers, impacting every aspect of the business–economics, business profitability, product design, technology, and engineering best-practices, not to mention overall brand value.
Innovation impacts growth

Manufacturing innovation can mean the use Lean and other cost reduction strategies. Increasingly, it means automation and digitization of manufacturing as we move toward the era of the Digital Factory and big data analytics. And, In today’s global landscape, innovation must include the ability to easily replicate processes across sites to ensure higher global quality standards and greater control, visibility and synchronization across operations.

How do you get there?

A key requirement for global innovation is a unified production environment across facilities. High Tech manufacturers that use different processes and production systems in their various facilities will have difficulty achieving innovation– effectively blocking all of the potential benefits. When different plants use different MES systems, for example, there can be little agility, as every change becomes a custom IT project.

Improve operations processes across sites

This is why High Tech manufacturing leaders have moved toward unified and standardized systems, so that process changes and manufacturing agility can be achieved faster and more easily. In such an environment, global shop floor operations can be unified through a Center of Excellence, which can then ensure comparable and measurable manufacturing standards on a global scale. As they say, you can’t improve what you can’t measure.

Measuring Innovation

Innovation can (and should) be measured on an organizational level. The implementation of manufacturing intelligence solutions is often justified by this single function, as part of a manufacturer’s quest to achieve better visibility across operations. The ability to measure is greatly enhanced when it is part of an overall innovation strategy, underpinned by unified technology.

High Tech manufacturers will want to measure several aspects of innovation, such as business measures related to profitability, innovation process efficiency, or employees’ contribution and motivation. Measured values might include new product revenue, spending in R&D, time to market, quality scores for suppliers, and growth in emerging markets.

Manufacturing Innovation

What is pivotal is that innovation must align with corporate strategy and global manufacturing performance in order to ensure continuous growth and return on investment. A well-defined innovation program, combined with an IT infrastructure that supports global agility, is essential for High Tech manufacturers that want to compete and grow in a sustainable fashion, now and in the future.

Now there’s a solution for greater visibility, control, and synchronization of operations. Visit the Flexible Production solution page and read the flyer to find out what a flexible global production platform for manufacturing can do for your High Tech enterprise.

Bringing Predictive Analytics to the Shop Floor: OK, but How?

By Christian
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Predictive Analytics can bring a lot of value to shop floor operations, especially to improve quality, yield or process sustainability, for example in composite manufacturing.

Machine learning algorithms allow to extract patterns from past production data. These patterns, which make up a model, can in turn be used to obtain predictions (“what is the risk to have a defective part?”) or even recommendations (“what can I do to reduce the risk?”).

Data Scientists wanted!

I have intentionally used the expression “machine learning algorithm” and you may think that companies that want to go in this direction need to hire a team of data scientists.

Indeed, many open source or commercial solutions require the availability of data scientist skills along with good programming skills in order to:

  • Identify the proper algorithms to use
  • Fine tune algorithms to get good results
  • Ensure scalability and performance

So it is no surprise that with the explosion of Big Data and Predictive Analytics, job postings in this field have skyrocketed since early 2012:

data_scientist_job_trends
Percentage of job offers with words “Data Scientist” or “Data Science” ©  Indeed.com.

And, as a result, salaries have soared and positions are hard to fill, which slows down the adoption of Predictive Analytics solutions.

Empowering Quality Managers and Process Experts

In order to overcome this difficulty, the DELMIA Operations Intelligence  solution for shop floor optimization (DELMIA OI) has been designed from the start for Quality Managers and Process Experts. There is no need to select or fine-tune algorithms and “correlation” is probably the most complex word used in the User Interface. Training is achieved in a few days.

shop_floor_quality
A failure analysis engineer prepares boards for corrosion testing. © Intel.

We also think that expertise is essential to obtain reliable models in the manufacturing field. For example, a process expert may identify irrelevant parameters, add relevant durations between operations, spot errors in data… And, last but not least, he may get inspiration from the model, which in the case of DELMIA OI comes in the form of human-readable rules.

Does this mean that data scientists are out of the picture? No, if you are lucky enough to have such resources, you will realize that best results are actually obtained by the collaboration between all profiles. Data scientists bring their experience on how to prepare and handle data, while quality managers and process experts can make informed decisions using their process knowledge.

The need for a Method

Even simple concepts and an intuitive user interface will not guarantee best results. You need a method to avoid pitfalls when you have to deal with potentially erroneous or incomplete data and different ways to address the problem.

Using the experience of DELMIA Operations Intelligence past projects, we have been able to build such a method, which has been recently shared in the DELMIA Enterprise Intelligence community.

The method consists in 8 steps:

understand_process
Understand process
import_curve_data
Leverage curves
 cleanup
Clean data
 prepare
Prepare data
 target
Define output
build_model
Build model
 validate
Validate model
 assess_value
Assess value

The method answers questions such as:

  • How to leverage curve data (hint: you may need BIOVIA Pipeline Pilot)?
  • Where should I put the frontier between a good and a bad yield?
  • How can I measure the reliability of the model (its ability to predict)?
  • How can I improve my model?
  • How can I evaluate the number of defective parts that could be spared if DELMIA OI recommendations were applied on the shop floor?

Discover more about how to build reliable predictive models to optimize your manufacturing operations by joining our free DELMIA Enterprise Intelligence community.

Once you are registered, it all starts with this post!

JEC World 2016 and Dassault Systèmes: Composites Disruptive Technologies

By Yves
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JEC World 2016, the N°1 worldwide Composites Tradeshow which took place in Paris on March 8-10th, 2016 was an exciting opportunity for Dassault Systèmes to connect with Composites users and influencers across Industries.

Either visiting the 3DS booth or attending the Design in the Age of Experience conference cycle, they could discover the value that our 3DEXPERIENCE platform for Composites and Additive Manufacturing provide to their business:

Extend & Strengthen the Composites Value Chain

The 3DS Composites integrated solution is known to span across the entire spectrum of composites product development, from design to analysis and manufacturing on a single virtual platform, with Best-in-class Partner solutions complementing the process. This year, along with our partners Galorath Inc. on the booth and Convergent Inc. across the aisle, we demonstrated further strengthening and extension of this value chain.

Composites Thermal Assessment - CONVERGENT Inc

 Composites Thermal Assessment – (c) CONVERGENT Inc.

For early feasibility assessment at Conceptual Design stage, Galorath showcased a Cost Estimation solution called SEER for Composites, while Convergent Inc. delivered Composites Thermal Assessment in the hands of Designers for quick decision making. Downstream in the process, several Manufacturing Design solutions were proposed to ensure seamless interaction with Shopfloor Systems, including the new Laser Projection Operator role from Dassault Systemes, increased interaction with JETCAM for output to Nesting and Cutting Systems, and Coriolis integrated CATFiber for Automated Fiber Placement.

Laser Projection - DASSAULT SYSTEMES

Laser Projection – (c) DASSAULT SYSTEMES

Drive disruptive technologies for Clean Energy

In line with its mission as charter member of IACMI – Institute for Advanced Composites Manufacturing Innovation – Dassault Systemes is also committed to develop lower-cost, higher-speed, more efficient manufacturing processes for advanced composites.

Composites Thermo-Forming - DASSAULT SYSTEMES

Composites Thermo-Forming – (c) DASSAULT SYSTEMES

Dassault Systemes recently released a dedicated solution for Composites Braiding and showcased during the show the upcoming capabilities for Thermo-Forming. These both position Manufacturing Simulation at the heart of the Design process to provide enhanced Experiences about manufacturability, increased trade-off for design exploration and in fine, to help drive clean energy product development & manufacturing.

Composites Braiding - DASSAULT SYSTEMES

Composites Braiding – (c) DASSAULT SYSTEMES

Enable Industrial Adoption of Additive Manufacturing

We also received a huge interest for our new Additive Manufacturing solution. This integrated value stream from science-based functional generative Design to Manufacturing process and Simulation really aims at solving some of the key challenges slowing down the industrial use case adoption of 3D Printing.

We demonstrated that combining Modeling, Simulation and Optimization in the hands of a Designer, we can remove the traditional barriers and provide huge gains in productivity. And that with digital continuity, from Generative Programming to Manufacturing Simulation & Optimization, we allow to regain control over the Manufacturing process and reach expected quality and repeatability.

Functional Generative Design - DASSAULT SYSTEMES

Functional Generative Design – (c) DASSAULT SYSTEMES

At the heart of Innovation with Partners Ecosystem

As an acknowledgement of this thought leadership, Dassault Systemes received during the event the prestigious JEC World 2016 Innovation Award for its accomplishment on Large-Scale Composites Additive Manufacturing innovation with OAK Ridge National Laboratory (ORNL) and Cincinnati Incorporated.

JEC World 2016 awarded DASSAULT SYSTEMES

JEC World 2016 awarded DASSAULT SYSTEMES 

ORNL, Cincinnati and DS developed a revolutionary platform called Big Area Additive Manufacturing (BAAM) which makes possible to 3D-Print large products like the Shelby Cobra in a few hours. Material is added 200 times more quickly than with existing systems and production costs can be cut by 95%.

JEC 2016 award to Dassault Systèmes

For those who missed us at JEC World 2016, you can still connect with Dassault Systemes on these Composites and Additive Manufacturing topics, amongst many more Experiences, during the DESIGN In The Age of Experience event on April 11th-12th, 2016 in Milan. And we will soon make the recording of our JEC conference cycle available on the 3DS Composites Community. Stay tuned …



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