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 …

[PART 2] DELMIA Helps the Aerospace Industry Meet the Challenges of Composite Manufacturing

By Christian
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Composite wing flap at Airbus
A composite wing flap in Filton, Bristol.
Source: Department for Business, Innovation & Skills, UK.

I’m Christian Chaplais, Senior Manager of R&D DELMIA Enterprise Intelligence Applications. Welcome to the  second blog  of a two-part series on how  Operational Intelligence is helping the Aerospace & Defense Industry.

Finding a Way Around the Complexity of Composite Manufacturing

Many composite parts manufacturers have been exposed to quality issues for years. Some have used classic approaches such as simple statistics, advanced statistics or optimization consulting services to find an answer, but came up short.

So, the question remains. How do you solve composite manufacturing issues without going through all the complexities? There is a way to discover and apply an empirical (data-based) model without the complications in just a few weeks: Operations Intelligence (O/I).

With (O/I) Process Rules Discovery, for example, quality engineers or process and product experts can discover patterns (or rules) explaining whether results have been satisfactory or not. This can be done with a limited number of observations, which keeps down costs, in a ramp-up study.

Process and product experts can also understand the model with Process Rules Discovery, change it by editing the rules and immediately see the impact on the rule KPIs (Key Performance Indicators) based on facts (data).

Here’s a sample rule discovered by Process Rules Discovery:

sample rule

The rule can be interpreted as:

When the product is in the autoclave for an extended period of time (cure cycle time is high)…
…and the binding strength of the fiber is low,
…and fibers have been aging sufficiently,
then the quality is good.

Let’s take another O/I example. With Operations Advisor, shop floor workers can assess risk and take preventive or corrective action in real-time. Operations Advisor recommends values for actionable parameters (settings) without requiring any change to the process specifications or investment in new material.

operations advisor

[Operations Advisor risk assessment and proposed settings ranges (in green)]

Adopting Operations Intelligence

The DELMIA Operations Intelligence solution for Composites has been widely adopted by the Aerospace & Defense Industry from both OEMs and tier-one suppliers.

For several years, one company has been faced with an important and repetitive nonconformance issue (delamination) on the composite leading edge of wings for an aircraft manufacturer. On this family of products, the reject rate could reach 13% and the rework rate 28%. There were delays (up to 6 months of manufacturing backlog), extra internal costs, a loss of confidence from the customer and internal frustration. Multiple quality tasks including process audits, investigating new processes, SPC analysis, inspections of raw material, etc. did not solve the problem.

They then decided to use Operations Intelligence to analyze two years of production. In less than six weeks, two influent parameters, unsuspected until now, were identified (the fluidity of the resin and the time during which the part is kept under vacuum), as well as the recommended lower and higher limits for these parameters. By applying the rules discovered, they managed to instantly reduce the scrap rate to zero and the rework rate to 1%, removing any backlog shortly after.

I’d like to hear your experiences with Composite Manufacturing? What was the outcome?

Continue the technical conversation. Join the DELMIA Enterprise Intelligence Community: https://swym.3ds.com/#community:453

 



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