Clearly, earlier industrial revolutions were all about making better use of resources (e.g. burning coal to make steam), people (e.g. workers in factories) and, latterly, electricity and computer-controlled automation. For each revolution, the companies that did well were early adopters of the technology and practices of the day, and they recognised waste when they saw it.

So, what’s going to be the secret of success under Industry 4.0?

My resounding answer is Data. Or, more specifically, making better use of data.

In the world of engineering, many companies store their design data within their organization’s Enterprise Resource Planning (ERP) system. But the ‘resource’ it focusses on tends to be people and materials. Because of this, most engineering departments also use complementary solutions for Product Life Cycle (PLM), Product Data Management (PDM), Material Requirement Planning (MRP) and Document Management Systems (DMS).

However, there often is an alarming disconnect between the systems I’ve just mentioned and the tools engineers use, such as MCAD and ECAD systems – especially, if we go beyond traditional mechanical engineering into the domain of cyberphysical systems that comprise mechanical, electrical and software components. We know this because of the huge amount of time we, as engineers, spend on admin tasks. At Zuken we had an idea that this was a big problem, from talking to our customers. Indeed, a study we commissioned last year revealed worryingly that engineers spend only around half of their time on core engineering tasks.

What is an Industry 4.0 company?

I’d define one as:

1. Extremely dynamic, flexible and responsive to real-time market needs;
2. Having no physical/geographic limitations, as it is connected to sister companies, partners and suppliers via the Cloud;
3. Having seamless exchanges of data between all essential engineering design tools and PLM, ERP, PDM and DDM tool etc; and
4. Actively discouraging emails and phone calls in relation to any given project.

So, imagine life within a company that has really bought into Industry 4.0.

All design activities create or modify data that is shared with others. All other stakeholders see their respective subset of that shared data. Also, providing suppliers and contractors with restricted views (of that data) means bidding can start the instant a design is finalised. Moreover, no one need worry about the flow of the data because automated processes will greatly reduce (and ideally eliminate) the amount of time spent on admin tasks.

Under this fourth industrial revolution, making poor use of data will be as inefficient as having leaky valve seals on a steam engine under IR1, living with faulty electric motors under IR2 and incorrectly programming production line robots under IR3.

Further reading

• Find out how under Industry 4.0, maintaining and upgrading plant and equipment will become easier by making better use of engineering design data, in Maintenance: A design for life , by Marco Canducci, Industrial Plant & Equipment magazine
• Engineering Data Management guidance from Zuken

The post Data – The Secret of Success Under Industry 4.0 appeared first on English.

The following excerpt is from Andy Shaughnessy’s interview with Zuken’s Humair Mandavia in the April 2018 issue of Design 007 Magazine. 

Zuken has been developing PCB design tools for the automotive market for years. With automotive electronics worth over $200 billion globally, and growing every day, Zuken is preparing for a brave new world of smart cars, and autonomous and electric vehicles. I spoke with Humair Mandavia, chief strategy officer with Zuken, and asked him about the challenges facing automotive PCB designers, and the trends he’s seeing in the constantly evolving segment of the industry.

Andy Shaughnessy: Humair, tell us a little bit about Zuken’s work with automotive PCB design. I was at Zuken Innovation World a few years ago, and all of these automotive people were there, from Ford to Continental Automotive Systems, and the attendees were from all around the world.

Humair Mandavia: We’re fortunate to be working with most of the major OEMs and the tier one suppliers supporting the automotive industry globally. Zuken has been emerged in this market for over 20 years, and it’s been an area of significant growth year-over-year. As part of that growth, there are three key technology concentrations that have been part of our enablement too support the automotive market…

Read the rest of the interview here

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Checkpoint or Milestone Releases to PLM

There are multiple times during the design process when design data should be packaged and placed in the PLM system.  The most frequent release type is a daily or weekly checkpoint. This entails packaging up the data for archival purposes.  Another common release type is driven by a milestone such as a design review.  Design reviews can be done through the PLM system given the number of potential stakeholders. This require a release package that contains schematic and board viewables and a current BOM at a minimum. Specifications, simulation results and various other documents may need to be provided based on the review type. When the review is completed, mark-ups, instructions and BOM changes need to be passed back to the design team.

Release to Manufacturing

The release to manufacturing process can come in at least three flavors: prototype, first article and full production builds. A release to manufacturing PLM package contains the schematic and PCB viewables plus the entire fabrication package for the board. Depending on your manufacturing process, your list could include fabrication outputs such as drill, ODB++, Gerber, fabrication and assembly drawings and of course a BOM.

These release points occur repeatedly throughout the design process and the release package content generation is typically a manual process..

Common Pitfalls

• Are we sure that the design files used to generate the outputs are the latest version?
• Are the board, schematic and EBOM in sync?
• Are there procurement or lifecycle issues with any of the components used in the design?
• Have there been recent footprint updates that need to resolve?
• Have I produced all the required outputs?
• Is my process repeatable?

There’s a Better Way

An advanced engineering data management system such as Zuken’s DS-CR has much to offer and can help solve many of these issues. By incorporating vaulted work-in-progress (WIP) design data, you can overcome many of the more common pitfalls in the process:

• Ensure that the correct design files are in play. The WIP vault keeps the latest version current.
• Add approval controls to your design data. Design data can be reviewed and approved prior generating release packages.
• Provide an audit trail; you will always know who did what and when.

DS-CR’s intelligent EBOM is directly related to the schematic and board layout. These items are checked and kept in-sync throughout the design and release process. The EBOM is directly tied to your corporate component library allowing you instant visibility into any possible component lifecycle issues.

Document generation is automated and works directly on your vaulted design data. It is template-driven ensuring that each release point has all the necessary outputs.

Object-based notifications will inform you of changes that might impact the integrity of your design. Here are a few examples:

• A component library part changed after the schematic was last vaulted.
• There has been a footprint change after the board was last vaulted.
• There has been a schematic change after the board was last vaulted.
• The EBOM and schematic have been modified by different people.

As you can see, engineering data management systems such as DS-CR are essential to ensuring a smooth transition between your design process and PLM release points. The fact that you can fully trust content and source data will lower your risk and just might let you sleep better tonight.

The post Controlling the Release Points for Your PLM/PDM System appeared first on English.

In Part 1, I looked at the benefits of predictive failure analysis, along with a real world example using a typical home furnace. Now I’ll look at how you can move your product development process forward to take advantage of predictive failure analysis and, ultimately, improve your product quality? You may be surprised at how easily you can get game-changing benefits by making some design process changes and using proven technology…

Step 1: Switch from component-based design to function- or modular-based design

Today, electronic hardware is typically designed by placing components on a schematic. Moving to a module or function-based design process has a number of benefits. Modular design alone enables reuse and faster design cycles. But combine modular design with a design data management (DDM) platform and the benefits expand to include ownership, history, version control, and where-used and user-defined data. It’s like supercharging it! If there is a problem with the module, a DDM system enables comprehensive problem resolution by identifying every product that uses it.

Another key benefit is the notion of continuous improvement. The module owner can continually improve the quality (e.g. reliability, cost, manufacturability) and that change history is part of the module’s annotated data. The module’s annotated data also contains diagnostics that exercise the function and become part of the field diagnostics package. So if we stick with our example of the home furnace, it runs diagnostics on a module by module basis and reports back diagnostic codes that can identify the failures. Modular design is an emerging trend that should be considered with or without adoption of predictive failure analysis.

Step 2: Establish the IoT platform and the Cloud

This step goes beyond the scope of Zuken’s solutions and will require a partner. In this case, PTC offers an IoT Platform called ThingWorx®. The IoT platform provides the linkage between the device and the PLM system and, ultimately, to the design team via a design data management solution (e.g. DS-2).

In this case, the furnace runs diagnostics on a periodic basis and reports back the results and environmental conditions to the IoT platform, which is the collection point for the connected devices. It collects the data and runs analytics to determine if we have a failure trend that can be identified. We’re considering a manufacturer monitoring 500,000 furnaces, so let’s say the furnace population diagnostics indicate the gas control module on the furnace appears to be failing regularly at 5,000 heating cycles or about 4-5 years of usage, but it is designed for 20,000 heating cycles. The IoT platform is connected to the PLM system and that information is attached to the design record for this furnace model. If you have a design data management system connected to your PLM system, that gas control module performance record can be attached directly to the design module as annotated data. The design team now has everything they need to improve the quality of the gas control module.

Step 3: Device to Cloud Connection

As in step 2, I’m going to reference one of our partners to provide the device connectivity to the IoT platform. PTC’s Kepware® provides the communication channel for managing and monitoring your connected device. The furnace simply uses the Kepware connection to log diagnostics and environmental conditions to the cloud.

This is possible now!

The exciting part is that we can now measure the product performance in the hands of a customer, not just in the lab. Predictive failure analysis is attainable today. The pieces exist. But it does require a change in your design process from component-based to module-based design, which should be considered on its own merit. The IoT pieces are available and proven. Remember, the connected device has already been implemented and utilizes “Apps” that we all commonly use. We are just applying the same connectivity for the purpose of field performance measurement.

The opportunity exists now to measure and improve your product quality.

The post Predictive Failure Analysis Can Improve Product Quality: The Reality – Part 2 of 2 appeared first on English.

Techconsult, a German-based analyst firm has just found that almost half of the engineering time of any manufacturing company is spent feeding systems and re-entering data. So it’s no surprise that economists are scratching their heads trying to explain why productivity is declining, despite constantly increasing investments in IT systems.

Complexity stunts productivity

We asked Techconsult to look into this, so they spoke to more than 150 engineering managers to find out where the problem lies. The answer: The complexity of products and processes is increasing, putting engineering productivity under pressure. Design re06use seems to be a viable solution, but the managers doubt that the available systems will help them.

This is bad news – but it gets worse. In the information age, the common cure for any problem is to throw a piece of software at it. In the case of engineering, the consensus was: Map the product development process in a system, manage the design data, and this will solve the issue. But the survey data doesn’t bear this out, finding that 77% of engineering decision-makers expect to gain no positive productivity effects from a PLM system.

Admittedly, I’m not surprised by this outcome (though I was expecting a little more positivity). But it is completely in line with my day-to-day customer experience. From the Zuken perspective, it has always been an issue that the workflows and requirements of electrical and electronics engineering were not covered by PLM systems, opening a dangerous gap where there should be a seamless cross-discipline flow of design data and process information.

The good news

So, is there any good news here? There is, and it comes in a clear statement from the engineering managers surveyed by Techconsult: 78% believe there is value in dedicated design data management for electrical and electronics engineering, tightly integrated with a PLM system (and equally tightly integrated into the ECAD system, I would add). This is what we call domain data management at Zuken. It’s just a fancy term for electrical and electronics engineers managing their own data and workflow from within their own tools. It’s something we’ve been doing for electronics engineers for a long time, but now we’re making it truly cross-discipline by adding a dedicated tool for electrical engineers, with DS-E3.

We knew the need was there, and we had an idea that companies were beginning to understand where the gaps lay in their systems, but as Robert Heinlein said: “Being right too soon is socially unacceptable.” I guess the time for domain data management has come. Finally.

Find out more at www.zuken.com/edm or watch our new movie

The post Design Time vs. Admin Overheads: How to Win the Battle by Closing the Gaps appeared first on English.

Today I’m going to take a step-by-step look at some circuit module reuse best practices, along with an example. The answers that I’ve kept you waiting for in part 1.

Managing modular circuit blocks

An increasingly popular and effective way of dealing with human errors creeping in when reusing designs (such as inadvertently using older block prior to an issue being resolved) is by using data management software that stores reusable circuitry as modular blocks. This greatly simplifies the process of reusing existing PCB schematics, parts lists and layouts.

The new generation of data management software controls access to circuit blocks, so only authorized editors can make changes. Editors need to check out the modular block and other users can’t make any changes to it until it’s checked back in, to ensure the design integrity. The software can also be configured to require approval when a change is made to a modular block.

Reusable modular blocks can be created in two different ways:

Top-down approach

1. Partition the design early on in the design process.
2. Create the block diagram, then add circuitry to each block.
3. Validate blocks and complete the design.
4. Register the parts list, schematic and layout of each block in the data management system, along with its metadata containing detail such as which products the block is used in, engineers involved in its design, and the approval chain.

Bottom-up approach

1. Create and validate the circuitry .
2. Partition the design into blocks.

You can see  how much more effort the top-down approach takes (four stages rather than two), and it requires more planning time. But the payoff is huge in that blocks produced this way are usually much more suitable for reuse, so you save lots of time later on when you reuse the blocks in variant designs. Put the work in at the start to reap the benefits later on down the line.

Streamlining the design process – cell phone example

Let’s look at how the modular design approach can substantially help streamline the design process for the cell phone example mentioned in part 1. We’ll assume that the design has been partitioned into blocks representing the RF, baseband, Wi-Fi, Bluetooth and other sections.

The engineer working on the new variant follows this simple process:

1. Call up the modules by searching the data management system for the product name.
2. Check the documentation stored in the system for each module they want to use, to ensure it is a good fit for the new design.
3. Drop the modular blocks into the new design. The parts list, schematic and layout of each modular block will all be incorporated into the new design.
4. Design the new RF block and any other new blocks needed, either from scratch or by modifying existing blocks.
5. Connect sections together and route new areas of the design.
6. Check the design
   1. Check for issues such as signal integrity and thermal management, focusing on the newly-routed areas.
   2. Do a basic simulation of the complete design; even though checked modules are used, there’s a small possibility combining them could cause an issue.

By designing this way, regulatory compliance time can be reduced by using proven design blocks. This reduction in design time means it’s possible to bring products to market faster, which helps increase revenue and enables new products to gain market share before they face serious competition. Modular circuit reuse also reduces errors by allowing designers to use proven designs wherever possible.

Is now a good time for you to make best use of modular design to help your team develop and release boards faster?

Learn more about engineering data management here, and view our webinars.

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