The manufacturing ecosystem is changing fast, and as supply chains and economic factors realign after Covid, how manufacturers make things, and where, is more important than ever. The digital transformation of manufacturing worldwide is accelerating, and it’s happening against a backdrop of constraints such as labour shortages, broken supply chains, and sustainability issues. 

Engineering.com’s Jim Anderton asked Arjun Chandar, founder and CEO of IndustrialML, about where AI and machine learning will take manufacturing in the future.

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What does it take to design appealing consumer products? For decades, manufacturers of everything from motor vehicles to laundry detergent have used market research tools such as focus groups to discover what consumers want. And it’s always been an expensive and uncertain tool for product designers. 

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Metal additive manufacturing has come a long way. From a classroom curiosity, it’s evolved into a go to part making method for many advanced industries like aerospace and healthcare. Traditional constraints like material availability, speed, resolution, as well as cost have been largely addressed in many applications. It’s viable and cost-effective, but what will it take to move this technology into the forefront, ahead of traditional subtractive technologies like CNC machining? 

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Photochemical etching has been around for decades as an engineering technology to create fine structures. It’s conceptually simple: impress an image of the desired structure on a metal substrate, using inks or coatings that are chemically resistant, then immerse the entire substrate in a strong etchant that will dissolve away unwanted material, leaving behind a high-resolution and complex part that can be extremely small. As a micro machining technology, it can do a lot more than manufacture watch springs, and to discuss this interesting technology and advanced applications. 

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The need to protect software from malicious attack is obvious for critical applications in the military, aviation and industry. As AI progresses and software takes over control of tasks like driving and operating robotics, the risk of wide scale attack increases. How can the software be protected against the threat? 

The post Software Security for Autonomous Vehicles: It’s Safety Critical appeared first on Engineering.com.

The transition to an all-electric economy will require two things: clean energy generation, and effective energy storage. The latter, batteries, represent the limiting factor in the adoption of electric vehicles worldwide. 

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For grid scale electricity production without CO2 emissions, there are several options. Wind, solar, hydroelectric, and geothermal are all viable technologies, but they are dependent on proximity to key resources, namely water, wind or sunshine. Nuclear fission has offered clean power generation without these constraints for over 60 years, and a new generation of small reactors promises to remove the disadvantages of waste disposal and cost associated with older reactor designs. 

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Over a decade ago, Elon Musk coined a new term for large factories: Gigafactory. Since that time, Tesla has built giga factories in China, Texas and in Germany, with a plant in Mexico to follow soon. The very large manufacturing complex has its origins a century ago with large automakers like Ford, but the trend toward outsourcing of ever larger assemblies suggested a trend toward smaller, decentralized operations. Tesla uses a model geared toward vertical integration, and with the breakdown of supply chains during Covid, keeping more production in-house has shown to have definite advantages. 

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It is generally agreed that to make humanity a genuinely spacefaring species, the cost to lift mass to lower the orbit must be reduced by orders of magnitude compared to current systems. The original orbital launch systems were derived from ICBMs, characterized by high acquisition costs, complex engineering and huge technical institutional overheads, maintaining a very modest lunch cadence. 

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Cities are much more than agglomerations of people, homes and businesses. As venues for social interaction and the engines of the modern global economy, cities can be considered almost as organisms, consuming inputs such as energy and generating outputs such as manufactured goods or IP. Cloud computing has leveraged the internet to create virtual networks for commercial and industrial computing. Can the same technology be used to streamline and enhance a city’s function? 

Dr. Wilfred Pinfold, chair of the Association for Computing Machinery’s Smart Cities Emerging Interest Group, believes technology is the best method to create vibrant communities, deliver services and care resources, and create civic engagement. Dr. Pinfold describes the path to better cities.

The post The Future of Cities is Smart appeared first on Engineering.com.