Manufacturing in Asia is rapidly evolving. China maintains its strong position, and yet the rising cost of labor also means new opportunities for emerging hubs like Malaysia, India, Thailand, Indonesia, and Vietnam, which Deloitte has termed the “mighty five” (MITI-V). With low costs and supportive policy environments, these burgeoning economies represent a fresh and formidable group of challengers for the manufacturing industry.
With competition fierce and supply chains ever more complex, manufacturers are under intense pressure to increase yield, reduce production errors and uncover new areas of competitive advantage. Innovation is essential; and in particular, manufacturers will find it tough — if not impossible — to get ahead without embracing artificial intelligence (AI).
AI is already making an impact within our daily lives; from improved spell-checks when typing a text message, to traffic predictions on your favorite map app. With AI enabling computers to mimic human abilities and machine learning driving knowledge acquirement, reasoning and decision-making, the possibilities for AI-led cloud applications in manufacturing are vast.
Cloud applications which have AI baked into their existing processes are now enabling organizations to take a pioneering, automated approach that eliminates the boundaries between transactions, analytics and decision-making; simplifying operations, and providing astounding visibility across the entire process of production. With AI-led deployment of a self-learning model, manufacturers can create a culture of quality and lay the path to continuous innovation in the future.
A useful metaphor to understand the value of such technology is baking. When a cake comes out of the oven with a defect — perhaps it’s burnt, collapsed or unevenly cooked — the baker must guess what went wrong, then try again. Only through trial and error can the perfect cake be achieved, but in the meantime, the baker is wasting a huge amount of ingredients, electricity and valuable hours.
Now imagine if the baker could analyze every variable to understand what went wrong the first time. This is what AI and machine learning allow manufacturers to do; albeit with production, rather than cakes.
When manufacturers are able to spot anomalies during production, pinpoint the root cause of issues and predict events before they occur, the revenue benefits can be massive.
McKinsey reports on the situation of a chemical manufacturing plant which built an advanced neural analytics model that helped it identify how external weather factors were affecting the efficiency of the manufacturing process, eventually leading them to upgrade a single piece of equipment. This saved the business nearly $590,000 in value annually, in an investment that paid for itself within 12 months.
AI cloud applications are already improving yield for biopharma manufacturers, making semiconductor chip testing more efficient and helping car part makers predict and avoid safety incidents before they occur.
Today, there is simply no better way to integrate complex supply chains, extract actionable insight from a mammoth collection of data, and use it to better the business. As the Internet of Things continues to generate vast amounts of data, it will be increasingly difficult to extract the most possible value from all that information without AI.
Along with easing the process of regional and global expansion, the new generation of cloud applications infused with AI can help manufacturers get smart about quality control. AI is invaluable to quickly uncover the root cause of errors and ensure they don’t happen again. Indeed, with rising margin pressures in consumer-oriented industries, companies can’t just be good at quality control ? they must be fast, and intelligent. This is where AI comes in.
Cloud-based manufacturing apps infused with machine learning and AI are saving time and money for businesses. Previously, in order to remedy an error or effect a beneficial process change, manufacturers had to gather many different teams to analyze vast amounts of data from different systems; in a process that could take weeks or even months. Now, thanks to emerging cloud technologies which bring together and analyze structured, semi-structured and unstructured data from multiple data sources, manufacturers can understand the root cause of a problem in as little as a few hours.
Using technology to drive a culture of quality is now essential for manufacturers. IDC reports on the future of manufacturing: “By 2020, 60% of G2000 manufacturers will rely on digital platforms that enhance their investments in ecosystems and experiences and support as much as 30% of their overall revenue.”
IDC researchers also note that by 2020, “80% of supply chain interactions will happen across cloud-based commerce networks, improving participants’ resiliency and reducing the impact of supply disruptions by up to one-third.”
As Asian manufacturers compete to capture new opportunities, being quick, agile and proactive will be more important than ever before. With AI-infused cloud applications, smart manufacturing is now accessible to every manufacturer ? enabling them to gain visibility into real-time conditions and production efforts, and then react to that information with the speed required to deliver products that customers want with the efficiency they need. AI and machine learning are driving Industry 4.0. They are key to powering Asia’s economic growth engine for today, and tomorrow.
The author is the head of apps for Oracle Philippines
— Source: IDC FutureScape: Worldwide Manufacturing 2018 Predictions, Oct 2017
