As an experienced user of early version of the Motion Analyzer, I used the software as a tool to analyze tradeoffs between time, torque and inertia to optimize customer machinery and processes in motion control applications.  Good motion control starts with good mechanical design, and there are so many variables and tradeoffs, that it’s often difficult to navigate your way to the best solution.  A good motion analysis tool automates the process so that you can examine an axis requirement and explore several options for how the axis can be optimized.

The results of the Motion Analyzer can be directly integrated into the PLC editor RSLogix.  This is usually an area where there is a major duplication of effort, since everything that you have to program in the control system is data that you have worked with in the Motion Analyzer.  So kudos to the Rockwell team for getting this feature added to the RSLogix suite.

The Motion Analyzer uses information about the Rockwell Automation motors and amplifiers to match inertias to loads and duty cycle requirements to the thermal capability of the equipment.  This is an often overlooked subltety of the equipment, but at the end of the day, it’s all about the amount of heat you can get rid of.  And the duty cycle contains all the critical information about how much energy you need, when you need it, and how long you have to dissipate it.  In addition, I have found that everyone’s idea of thermal modeling is different.  So it pays to do the simulation work at the front end of the design.

But, we always used to joke that we were doing solid modeling anyway.  Everything was a cylindrical object of a certain diameter, length, material density, etc.  So it stands to reason that integration with a 3D modeling system would make sense.  After all, a little step up in capability could lead to a lot better design work from the start. And the ability to link mechanical design at the earliest part of the design cycle, directly to the output at the motor and control system, makes for better outcomes every time.

Today’s manufacturers are using a mechatronics-based approach to integrate the electronic, mechanical, and software components of their increasingly complex products. Digital prototyping allows disparate engineering teams to work from a single digital model, saving time and reducing errors throughout the design process. The Autodesk solution for digital prototyping enables manufacturers to achieve the full benefits of mechatronics product development.

The need for a new approach
Today’s manufacturers face unrelenting pressure to continuously develop innovative new products. According to a survey of CEOs, two-thirds of executives believe that innovation is vital to the future of their companies. Their concern is understandable; according to one estimate, the products that generate nearly 70% of revenues today will be obsolete by 2010.

In response to this call for innovation, manufacturers have accelerated their adoption of electronics. Research shows that 92 percent of manufacturers now incorporate electronic elements into their products.

The automotive industry provides a prime example. While the proportion of a car’s cost that can be attributed to electronic systems has increased by an average of 8.3% per year over the past eight years, the proportion attributed to mechanical systems has decreased by an average of 3.2%. These trends are broadly consistent across all industries.

As manufacturers respond to the demands of the market, they must deal with the added complexities of synchronizing mechanical, electronic, and software elements into one integrated system. In the process, they must effectively coordinate disparate engineering teams. A mechatronics-based approach can help.

Effective mechatronics product development demands a focus on three key engineering activities:
• Multi-Disciplinary Design and Engineering. Mechatronics refers to the integration of control systems, electrical systems, and mechanical systems. A mechatronics system is not just a marriage of electrical and mechanical systems, and is more than just a control system. It is a complete integration of all of them. Top-performing manufacturers are 3.2 times more likely to allocate design requirements to systems.
• Managing Communication and Workflow. Integration of systems should be coupled with improvements in the coordination between the discipline-specific teams that are responsible for creating individual subsystems.

The often complex inter-relationships between individual sub-systems demand effective communication and clear ownership.7 Top-performing manufacturers are 2.8 times more likely to communicate change among their engineering disciplines.8
• Effective Early Validation. If manufacturers are going to develop cheaper, more reliable, and more flexible ystems, they must validate across the traditional boundaries of mechanical engineering, electrical engineering, electronics, and control engineering at the earliest stages of the design process. Top-performing manufacturers are 7.3 times more likely to digitally validate system behavior.

The mechatronics advantage
Manufacturers that harness the best practices of mechatronics can achieve significant benefits. Best-inclass manufacturers are more able to reach their targets for development costs, product revenue, and product quality, and to hit their product launch dates. Such manufacturers can also:
•  Add more features and functions.
•  Reduce the size, weight, and cost of their products.
•  Improve their overall efficiency.
• Leverage adaptive control and diagnostics to improve reliability and reduce maintenance costs.
•  Customize or upgrade products by reprogramming embedded firmware.

In addition, a mechatronics-based approach mitigates risk and solves common design challenges such as the slow, serial machine design process; poor communication between machine designers and customers; and risky physical machine testing.

Challenges of adopting a mechatronics approach
As manufacturers focus on improving their mechatronics product development processes, they often face significant challenges:

Finding design conflicts across disciplines depends largely on the knowledge base of the staff—and yet manufacturers list a lack of cross-functional knowledge as their leading challenge. Although hiring issues are partly to blame, manufacturers seldom have design tools that can integrate design data from all the elements that make up a product. As a result, their teams fail to understand the impact of design change across disciplines.

If manufacturers are going to achieve all the benefits of mechatronics product design, they clearly need technology solutions that enable their design disciplines to collaborate and communicate seamlessly, while also helping them identify system-level problems early, verify that all design requirements are met, and predict the behavior of the final product.

Key elements of a mechatronics solution
Ideally, a mechatronics solution should support the following best practices:
1. Multi-disciplinary design and engineering
2. Managing communication and workflow
3. Effective early validation

Multi-Disciplinary Design and Engineering
As the saying goes, “If you don’t know where you’re going, you’ll end up somewhere else.” In product development, knowing what you need is the first step to getting the final product right. Outlining product level requirements is necesssary to achieve the first step in outlining product performance. The ability to drive these key parameters into system and sub-system operational performance goals is often what sets leading manufacturers apart from their peers.

Many manufacturers assume that building a single, integrated design process across all disciplines is the best way to coordinate multi-disciplinary design and engineering so that all product requirements are met.

But statistics show that the extra effort spent on process engineering ultimately goes to waste. Instead, best-in-class manufacturers use separate design processes across disciplines in order to leverage the domain expertise of their designers. However, this requires that they be diligent in coordinating and synchronizing their engineering groups. This synchronization is key.

This approach is a best practice that should be adopted by other manufacturers seeking to improve their mechatronics design processes. From a practical perspective, this will require manufacturers to deploy focused engineering tools that allow individual disciplines to excel at their work, while providing the ability to share information easily. But it is not enough to be able to model these systems. System-level performance is usually a function of the disparate engineering and design needs of various sub-systems. Breaking down a system into its core constituents, therefore, demands some formality. As a result, it is essential to establish clear processes for effectively communicating changes, and to align collaboration and system engineering tools that can help make sure teams communicate changes effectively.

Managing communication and workflow
As manufacturers seek to coordinate and synchronize their separate engineering groups, there are many ways to bring information together. The average company often prefers to generate the bill of materials (BOM) from a customer database application. However, this method requires not only dedicated maintenance and support, but also manual synchronization of design information—making it complex and errorprone for a structure that contains thousands of parts.

Best-in-class manufacturers take advantage of discipline-specific structures for designing products. Rather than maintaining one large database across all groups, companies can use individual, discipline-specific databases that allow groups to manage their workgroup-level data and workflow at a local level.

But even the discipline-specific approach can create problems if manufacturers do not manage it correctly. Ultimately, manufacturers must strike a balance between providing the focus that engineering disciplines require and making certain that the data they create can be brought together easily.

Effective early validation
No one disputes that it is a good idea to resolve integration issues before committing money to tooling and manufacturing ramp-up. Leading manufacturers focus on resolving integration issues early in product development, and maintain this focus right up until verification and testing.

By focusing on validation, simulation, and verification earlier in the development process, manufacturers can avoid the costs and delays associated with resolving integrations later on. But to achieve these benefits, manufacturers must bring together a wide variety of design and engineering information for review. The goal is to synchronize the efforts of larger teams into single design reviews where all pertinent information is available at once. This is just one of the benefits of digital prototyping.

Driving mechatronics product development with digital prototyping
Rather than trying to integrate information from disconnected engineering systems, manufacturers can save time and money by enabling all their teams to work from the same digital model. Today, many best-in-class manufacturers are augmenting traditional physical prototyping by building digital prototypes. By tracking and comparing physical and digital prototype test results, these companies are gaining a deeper understanding of their products and the environments in which they operate—leading to greater overall product quality.

How digital prototyping enables best-in-class manufacturing
According to recent research, best-in-class manufacturers that use digital prototyping outpace averagemanufacturers by:
• Building 50 percent fewer physical prototypes.
• Getting products to market 58 days faster.
• Reducing prototyping costs by 48 percent.
• Freeing up time and resources for greater innovation.13

An action plan for mechatronics excellence
Although manufacturers have been talking about the benefits of digital prototyping for many years, the ability to build and test a true digital prototype has, until recently, been beyond the budgets of most manufacturing companies. In recent years, however, vendors have introduced increasingly practical solutions that are more attainable, scalable, and cost-effective than their predecessors.

Aberdeen Group has identified four key capabilities needed for best-in-class mechatronics product development:
• Implement processes to overcome the lack of cross-functional knowledge and promote better communication.
• Use simulation to identify system-level problems early in the design process.
• Manage design requirements throughout the entire design lifecycle.
• Accelerate the design of system controls with automated software tools and simulations.14

For all of these reasons, manufacturers should look for an integrated engineering suite that enables a digital prototyping workflow.

The Autodesk solution for digital prototyping
The Autodesk solution for Digital Prototyping helps mainstream manufacturers realize the full benefits of mechatronics by allowing them to quickly create and easily maintain a single, digital model. This model connects mechanical and electrical teams by bringing together design data from all phases of development for use across all disciplines. Because the digital model simulates the complete product, engineers can better visualize, optimize, and manage their design before producing a physical prototype.

As engineering teams work on the digital prototype, Autodesk’s data management tools integrate electrical and mechanical components into a single bill of materials (BOM). Using tightly integrated mechanical and electrical information, teams create more accurate 2D and 3D mechatronics designs in less time, enabling manufacturers to get to market faster.

Just as Computer Aided Design, CAD, has revolutionized the design process, it is growing in capability and impacting many other arenas of engineering. The first major extensions to CAD were integration of Finite Element Analysis, the ability to analyze loads on the parts being created.  And certainly, if the design software can model the complex aspects of loading, then animation of part motion can’t be a far reach.  And that’s the case today.

Solidworks and Autodesk, among others, offer motion animation capabilities to detect interference and verify functionality of the basic mechanical design.  These features offer great facility to the designer to resolve issues early in the design process before the more costly aspect of hardware fabrication begins.

The next important layers of any design cycle are simulation and analysis.  Tools have been emerging for some time both separately and in tandem with the mechanical design software to provide this functionality.  Simulation requires that the designer can input velocity displacement profiles which, in the mechatronics context, provides the basis for torque, acceleration force, duty cycle,  power supply requirements, and a host of other information can be calculated directly from the simulation environment.

This gives rise to the best part of the whole situation; you can analyze the information.  No hardware needed!  So it becomes possible to do a series of iterations as “What If’s” to explore various options in the construction of the project that can lead to results that might not have been anticipated in the original design.  Personally, I think this is where the fun is.  And once again, no hardware needed.

This is also a bit tricky since there aren’t very good rules for what you do next.  So, to a certain extent, you have to be creative as you go.  The bad news is that the universe that we are dabbling in is very complex, dozens of variables and tradeoffs that have to be explored.  So it can be rough going because each applications has its own unique features and considerations.

The fields of application have been extremely broad.  Simulation and analysis of electronics has been with us for a long time.  The complexities of modern semiconductors would be impossible without software tools.  But the emergence of comparable tools for mechanical analysis is relatively recent and vendors are ramping up capabilities and features to support the mechatronics community.  These advances are sure to revolutionize the performance of OEMs the world over.

Some of our best work is still before us.

Simulation work that used to require mainframe computing power is now generally available as an add on module to 3D engineering graphics products.  Most of the major 3D engineering design products include animation features that allow the user to build and move the parts in space exactly as they will do when built.  This gives the designer enormous capacity to focus on issues in the design where several alternative solutions may exist.  There are even some intelligent software products that help guide the selection of components to help the designer facilitate the examination of alternative methods of solving certain mechanical problems.

Pretty cool.

But some of the stuff that’s really difficult to ‘automate’ is the stuff that requires human insight.  It kind of begs the question “what it is intelligence”. The area I am concerned with is tradeoff analysis.  And this area of engineering is one for which the world of computer software and ‘artifical intelligence’ has not been of much help.

Tradeoff analyses are normally calculations done  that attempt to examine how, in a given system, performance changes as the values of two competing attributes are altered.   So we look at two variables and assign the minimum and maximum values and look at how less of one and more of the other changes the outcomes in a particular system under examination.

But implicit within this system is the fact that only two variables can be examined at a time.  And, of course, the systems we deal with are much more complex.  The optimization of an electric motor consists of 22 variables, some simple values such as the diameter and length, some more complex having to do with magnetic materials and the many variable needed to describe the electromagnetic field of stator, for example.

So to get more out of the situation we need some different metaphors for looking at motion control and mechatronics applications.  Enter: the triangle.  We go from 2 variables to 3.  But we have a simplifying assumption that any one variable may be temporarily held constant in order to explore the other two.

I came up with a tradeoff analysis for Time, Torque and Inertia.  Published a few years ago in another magazine and briefly mentioned in one of my Design World articles a few months ago.  Basically, Time, Torque and Inertia all interact in very straightforward ways, but the point was to examine the hidden assumption that Inertia was fixed.  This is usually not strictly true, but instead we assume it to be true.  And this assumption prevents finding alternative solutions that may be very attractive.

So by using a triangle, we can create an analytical tool that actually helps us to think about and to find solutions, challenge hidden assumptions and produce better motion control.

The unique abilities of the RT3 version along with the support provided by Reliance allow the scientists to concentrate on the research without having to spend time controlling and verifying the test system.

The compact closed loop motor system has unique abilities to share I/Os, perform complex coordinated motion and use mathematical notation to perform motion. The onboard memory and logic banks along with the integrated tuners, vector drive, amplifiers, 32 bit RISC processor and 50,000 count magnetic encoder provide an intelligent motor which delivers cool running and smooth motion.

For this application, the motor moves extremely slowly and has been programmed to complete a 400mm long inverse cosine motion profile over a 12 hour 24 minute period using a 0.1″ leadscrew. Using this feature the scientists are able to replicate the lunar tides found in underground oil reservoirs for their experiments.

Newer software programs intended for machine builders take advantage of mechatronic principles and easily blend the necessary and different engineering disciplines.

By John Pritchard, Global Product Marketing Manager
Kinetix Motion Control, Rockwell Automation

Traditionally, machines have been designed and built using individual mechanical, control, and electrical design teams — that work independently to produce separate pieces of the whole system. Often, the mechanical team will turn the design over to the controls team and hope they can integrate the software and controls before control and programming issues are addressed. The machine might deliver substantial performance and flexibility advantages, but typically the marriage of the mechanical functions with the control system is not optimal; it is merely sufficient.

Ratio analysis, from Rockwell Automation’s Motion Analyzer software, eases the selection of gearboxes, timing belts and ball screws. It provides an “at-a-glance” view of any necessary trade-offs.

A synergistic blend between the different engineering disciplines is needed to make the mechanical design and the electrical system that drives it work in harmony. Mechatronics principles can deliver this harmony.

With an interdisciplinary approach, machine builders can bring engineering processes closer together, to improve communication and expand the available knowledge base. Such an approach lets you configure and integrate the pieces up front and reduce the chance of encountering problems at the controls stage later that would require changes in the original mechanical design. This concurrent engineering approach lowers design and development costs, adds more functions, and produces a more robust, balanced design.

Better Input

A successful mechatronics design depends on the ability of a cross-functional design team to communicate, collaborate, and integrate. A single project team helps ensure collaboration that is more inclusive and removes many of the obstacles that exist between engineering departments — barriers that often restrict the exchange of ideas and the free flow of information.

Some machine builders even include automation suppliers during this collaborative effort and bring them on board early. With the supplier as a consultant, machine builders can leverage industry knowledge and standards expertise, as well as share best practices for the technology.

The Torque analysis feature shows where the motor “consumes” torque. Transmission losses are sometimes factored in, but rarely checked versus load losses. Torque analysis makes checking simple and enables rapid “what if” analysis if improvements are required. If the majority of the torque is used to move the load, the design is sound. If over 75% is lost in the transmission, it’s back to the drawing board.

Real World Analysis

Due to the complex relationship of forces and motion, a persistent challenge for machine builders is calculating accurate component and system lifetime estimates. Often, designers tend to either undersize or oversize components.

Advanced software tools, however, help size and select the appropriate motion control system for the application. With these tools, they simply enter information about the load and how it needs to move, and the software selects a suitable motor-drive combination.

Tolerance analysis plots application data, such as move time, mass, losses and ambient temperature, against “health parameters” for the system. The ability to see which parameter hits 100% tells them the limiting factor. The software rapidly analyzes the system’s tolerance to changes and alerts you to any marginal design issues.

From a pull down menu, scroll through catalogue numbers and select an actuator. Complex calculations and manufacturers’ specifications have been integrated. These tools also help them avoid oversizing by automatically choosing the right transmission ratio, which helps reduce design time and errors that would have to be corrected later.

In addition to sizing and selection, motion analysis software can offer simulation analyses. With simulation analysis, engineers can effectively investigate machine behavior and select a mechanical design, along with the controls and software that will maximize machine operation.

Similarly, dynamic thermal modeling (available in some software tools) can more accurately verify system operation by taking into account motor ambient temperature and altitude. This feature can be especially useful for machine builders exporting to countries with hot weather or fluctuating temperatures because it can help eliminate post-installation problems that weren’t identified during machine trials.

Other tools, like advanced tuning simulation, help predict how the machine will perform. With this feature, the engineers can rework any problems in the early stages before building the machine. The software emulates tuning an axis and then simulates the behavior of the load, motor, and drive. Then it factors in mechanical compliance or backlash for a realistic performance evaluation.

Several motion analysis programs offer simulation analyses, which helps machine builders define the relationship between mechanical components and system operation. Engineers can effectively investigate machine behavior and select a mechanical design, along with the controls and software that will maximize machine operation.

As current business drivers offer greater motivation for mechatronic development, forward-thinking machine builders are implementing the strategies and acquiring the tools needed to develop a more integrated design process. More importantly, the improved reliability and faster time to market that mechatronics affords means more satisfied customers and a more favorable bottom line.

Rockwell Automation www.ab.com/motion

By Richard Comerford, Electronic Products

The lesson of ancient Babel still resonates through the halls of design firms today: if you really want to screw up a project, make sure that everyone working on it speaks a different language. Having a common technical language to express design concepts and plans is essential to enabling a team of engineers to work together.

And before everyone goes off to work out the details of their particular part of the design, it doesn’t hurt to do an overall simulation of the design concept. This will help ensure that, when completed, a complex system can do the job for which it was intended.

Simulation Realities

Unfortunately, that isn’t always the case. As Mentor Graphics design experts Scott Cooper, Mike Donnelly, and Darrel Teegarden observe in their introduction to How to Model Mechatronic Systems Using VHDL-AMS, “Although use of computer models is a key for successful design of complex systems, [we] have observed that engineers are often reluctant to invest the time and energy required to develop such models.”

They believe there are two reasons for this situation. For one, until relatively recently there were no standardized modeling formats available for such work. For another, there is a preconceived notion on the part of most designers that simulation technologies are difficult to use productively, and that building models is even more difficult. The lack of a standardized modeling format was solved by an IEEE standard, the VHDL-AMS hardware description language. Described as rich-featured and powerful, it lets users develop useful models and create meaningful simulations without having to become experts in the language. Then too, it promotes model reuse by allowing users to store models, easily adapt them, and run them on various compatible simulators.

As to overcoming preconceived notions, it’s hoped that the following example based on material from the Cooper-Donnelly-Teegarden work previously cited will help convince designers that modeling is not too difficult.

VHDL-AMS Modeling

A VHDL-AMS model consists of two different types of program statements: an entity statement and at least one architecture statement. The entity statement defines the interfaces of the device being modeled in so far as they are relative to the simulation. Through the interface, the model can communicate with other models via its ports (pins). Any external parameters to be used in the model are also declared in the entity statement, and the name of the entity is typically the same as the name of the model itself. An architecture statement defines the behavior of the model. A single model may only have one entity, but may contain multiple architectures, with each architecture statement defining a different type of behavior.

To understand how these statements are created, consider the case of an ideal single-input, single-output power amplifier, whose gain equation is output = K * input. The entity statement for this amplifier would be that shown in Figure 1.

entity amp is
generic (
K : real := 1.0 -- model gain, a generic (parameter)
declaration
);
port (
terminal input : electrical;
terminal output : electrical -- port (pin) declarations
);
end entity amp;

Figure 1. Entity statement for a simple power amplifier.

In the entity statement (as well as the architecture statement), the keywords for the model are always given in boldface. Comments about the coding are always preceded by “–”, and the

descriptive comment, of course, is not used in the simulation. In the entity’s generic statement, the value of the gain (1) is declared, while in the ports statement, the input and output ports are described. The generic K is declared as type real, so it can be assigned any real number. The value 1 is a default value here, but models do not have to have default values for generics. Note that the entity begins and ends with the name of the model, in this case, “amp”.

Defining Behavior

Model functionality is implemented in the architecture section (Figure 2), whose first line of declares an architecture called “ideal.” for the entity called “amp.” The model developer chose the name “ideal” to indicate that this is an idealized, high-level implementation. The model’s simultaneous equations and other concurrent statements appear between the begin and end keywords.

architecture ideal of amp is
quantity vin across input to electrical_ref;
quantity vout across iout through output to electrical_ref -- declarations;
begin
vout == K * vin -- simultaneous statements;
end architecture ideal;

Figure 2. Architecture statement for a simple power amplifier.

In VHDL-AMS, the “==” sign indicates that this equation is continuously evaluated during simulation, and equality is maintained between the expressions on either side at all times. If multiple equations are used in a model, they are evaluated concurrently.

In the architecture statement, both vin and vout need to be declared (K was declared in the entity). Since the electrical terminals (input and output) of this model have both voltage (across) and current (through) aspects associated with them, these terminals cannot be directly used to realize the model equation. Instead, individual objects are declared for each, and these objects are then used to realize the model equation.

In VHDL-AMS, analog-valued objects used to model conserved energy systems are called branch quantities because they are declared between two terminals. Branch quantity vin is declared as the voltage across port input relative to electrical ground, specified as electrical_ref in VHDL-AMS models. Branch quantity vout is declared as the voltage across port output relative to electrical_ref.

In the architecture listing, there no quantity declaration for the input current, since this is supposed to be an idealized voltage amplifier model and acts an ideal load, not drawing any current. Since no branch quantity is declared for this current, the input current is zero. The idealized output can supply any current, so the through quantity iout is declared along with across quantity vout. The simulator will then solve for the instantaneous value of iout needed to ensure vout is the correct value for the expressions in the governing equation: vout == K * vin.

While it is possible to model with much greater complexity using VHDL-AMS, the inherent simplicity of the modeling statements do not create a barrier to their use. Hopefully, you’ll be interested in pursing the language further, in which case the references given in the Appendix will prove extremely useful.

APPENDIX

How to Model Mechatronic Systems Using VHDL-AMS, SystemVision Technology Series, Mentor Graphics, Series Editors Scott Cooper, Mike Donnelly, Darrel Teegarden, http://www.mentor.com/products/sm/techpubs/index.cfm

The System Designer’s Guide to VHDL-AMS: Analog, Mixed-Signal, and Mixed-Technology Modeling,. by Peter Ashenden, University of Adelaide, Gregory Peterson, University of Tennessee, and Darrell Teegarden, Mentor Graphics. http://books.elsevier.com/mk/default.asp?isbn=1558607498

“Fundamentals of VHDL-AMS for Automotive Electrical Systems,.” Online workshop presented by Mentor Graphics. Available from the SystemVision websitehttp://www.mentor.com/systemvision