The Product Design Centre significantly enhances the
CAD library that is already available to DesignSpark members and provides more than forty different kinds of content, including product data, environmental and lifecycle information, as well as 3D models, footprints and schematics. New product information will be available as part of all DesignSpark
subscription options including product datasheets; RoHS and Reach compliance status (Y/N); and 3D model and footprint data. Further component data – including lifecycle risk, environmental risk, RoHS and Reach compliance information, and DRC status – is available in both the DesignSpark Creator and DesignSpark Engineer options. In addition, even more detailed product information – including technical attributes, predictive lifecycle, product alternative, export compliance to HTS, ECCN and Schedule B, product change
and end-of-life notifications – is available as part of DesignSpark Engineer.
The cloud platform, which runs on Amazon Web
Services (AWS), accelerates Jaguar TCS Racing’s critical data analytics. To test and optimise the car’s setup and race strategy, Jaguar TCS Racing needs timely access to data, much of which is then tested using digital twin technology. During a race
weekend, the Jaguar TCS Racing team collects approximately three terabytes (TB) of data. Analysis of this data informs the car’s setup, which includes the powertrain, suspension package, energy usage strategy, and software. “An increasing number of companies are
investing in a long-term cloud strategy to gain a competitive advantage, and Jaguar TCS Racing is no exception,” said Varun Kapur, vice president and senior managing partner for Sustainable Manufacturing, TCS. “Formula E races are often won or lost by fractions of a second. Our cloud technology empowers Jaguar TCS Racing to make time-critical, data-driven decisions, that optimise
the performance of the Jaguar I-TYPE 6.” James Barclay, team principal, Jaguar TCS Racing, added: “Cloud computing enables our team to drive operational efficiency when developing tools for deployment across racing activity. Race events require an increase in available compute power as our systems and engineers actively work to manage and analyse the influx of data being generated on track. The compressed nature of Formula E’s weekend format means that access to data is time critical to provide insights on performance between sessions where available time can be just 45 minutes.”
6
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130
