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Design007-Apr2019

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14 DESIGN007 MAGAZINE I APRIL 2019 Additionally, we can envision predictive an- alytics finally becoming mainstream. What if you could apply empirical manufacturing and quality data on a new design to predict yield, cost, and reliability based on the technology, materials, and manufacturing processes re- quired? Unless the manufacturing data col- lected is applied with the same level of intelli- gence and automation back to design, Industry 4.0 will not reach its full potential. Smart data empowers automation, which drives efficiencies, even at a lot size of one. That is the whole objective of Industry 4.0. Why start your smart manufacturing strate - gy with a handicap? Insist on smart data in- stead. DESIGN007 Reference 1. "German Industry 4.0 Index 2018," a study from Staufen AG and Staufen Digital Neonex GmbH. Patrick McGoff is a market development manager for Mentor, a Siemens Business. David Wiens is Xpedition product marketing manager with Mentor, a Siemens Business. manufacturing expertise because it's built into the system. However, the manufacturing digital twin is not limited to a single supply partner. Ideal- ly, you would have a digital twin of all of your manufacturing partners' capabilities so that you could see an aggregate impact of your designs. Material optimization is another element of the digital twin. Being able to see the material utilization of the assembly panel design based on your fabricator's panel sizes gives you the ability to adjust the assembly panel configura- tion to lower your costs. A rotation of a board or a nesting of boards may permit you to get additional boards on every panel, and that equates to savings for you. All of this aligns with the objectives of Indus- try 4.0. In probably the best summary state- ment of Industry 4.0 that I have seen, Danie- la Schäffer of Murrelektronik GmbH [1] states, "Digitization is becoming a great opportunity for many companies. The challenge will be to digitize the right thing and use Industry 4.0 not only as a 'showcase object' but also as an in- strument for optimization." In the future, we can expect advances in au- tomation of the feedback from manufacturing. Today, the DFM rules are updated manually based on the manufacturing lessons learned. Looking ahead, it makes sense that if the qual- ity data has the same level of smarts as the DFM data, the DFM rules could be dynamical- ly updated based on user-defined criteria. Scientists believe that silicon could be the answer to your battery woes with the potential for a charge capac- ity 10 times larger than current lithium-ion batteries. But sili- con has a tendency to frac- ture and break with numerous charge and discharge cycles due to volume expansion and contraction as silicon absorbs and releases lithium ions. Now, University of Alberta chemists have published re- search that takes a critical step in solving this prob- lem, studying the effect of nanostructuring the silicon within lithium-ion batteries to understand the importance of size. Researchers examined silicon nanoparticles of four different sizes within highly conductive graphene aero- gels. The results show that the smaller the particle, the less likely it is to crack or fracture upon lithiation. The next steps are to develop technology for creat- ing silicon nanoparticles in a faster and less expensive way, making these tools more accessible for industry and technology developers. (Source: University of Alberta) Tiny Silicon Nanoparticles Cement New Era for Ultra-high Capacity Batteries

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