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Optimized Machine Capability Through Mechatronics: Packaging for the Future

Mechatronics can be defined as the science to optimize the performance and capabilities of machines using a multi-domain synergistic design approach. It is also described as the combination of mechanical, electronic, computer, software, control, and systems de - sign engineering. Simply put, this concept enables machine builders to produce machines that produce the highest quality at maximum throughput. Additionally, it empowers manufacturers to make incremental improvements to existing assets to ultimately meet or exceed core key performance indicator (KPI) targets.

altThe packaging industry has largely known about the concept of mechatronics for quite some time. The implementation and adaptation of mechatronics to this point has largely been on the design and development of new equipment, with particular emphasis on those machines requiring high-speed operation. The continual migration from the mechanical to the electrical necessitates this, but mainly from the standpoint of design versus machine optimization on the back end (i.e., existing machine optimization). As companies streamline and become focused on growth even during times of economic turmoil, it is imperative that alternate strategies be considered to remain ahead of the curve.

In the case of a mid-sized yogurt producer, the company looked to expand capacity as well as incorporate modest enhancements to improve core KPIs. This gave way to a mechatronics analysis to achieve key goals and give the once-struggling facility new life. The overall goal for this end user was to use the core principles of mechatronics to bring about a simpler and more reliable means of meeting the challenges facing many packaging companies today.

To begin the mechatronics analysis, a core set of steps was proposed by the Siemens Industry mechatronics team:

• KPI identification
• Identification of non-compliant areas in the overall process
• Finite analysis of existing mechanics
• Analysis of component electrical systems
• Analysis of communications architecture and data handling
• On a module level, begin to determine how to improve
• Design improvements
• Testing and re-testing
• Design improvements into specification

The scope of the mechatronics analysis was on the machine level, and a Siemens mechatronics engineer reviewed the entire process. Working with the original design, the core system was largely mechanical, and to increase productivity and reliability, there were many opportunities to seek improvement just by implementing a servo-based architecture. The decision was to leverage the capabilities of the Simotion and Sinamics platforms to achieve this with Siemens.

The planned change in design outlined the following steps relevant to sizing the system:

• Sizing of the motors and gears
• Selection of the electrical drive system
• Selection of the motion control system
• Design of the communications network

On the target machine, the completion of the design sizing yielded a system architecture that incorporated 12 new electrical axes, and a flexible industrial Ethernet architecture. The systematic coordination of these axes was only secondary to the need to ensure that regardless of the configuration, the system would come together to improve target KPIs, and increase productivity, asset flexibility, and reliability. To achieve this, the sample workflow shown in the figure was proposed.

Simulation: The Virtual Machine

The true power behind the science of mechatronics is the ability to design through simulation. This ability in itself has several key advantages to the customer and machine designer. The concept of the virtual machine was introduced to make the aforementioned workflow possible. Leveraging tools such as NX 6 Motion and MATLAB, the Siemens mechatronics engineer was able to build virtual prototypes and perform a complete dynamic analysis of the entire system before the first component was built or modified. The initial input into this tool was a 3D CAD model to formulate a finite element model. The use of these simulation tools enabled Siemens to integrate the controller and drive system — in this case, Simotion and Sinamics — as key pieces of the analysis and as a contributor to overall system performance.