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Editor's Pick(1 - 4 of 8)
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Welcome to the Third Stage of Cloud Evolution: The Rise of the Industrial Cloud

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Wireless Infrastructure for Industrial Applications

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From Robotics to Big data, what the future holds for manufacturing

By Karl Rosenblum Head, Global Capacity and Risk Strategy, Alcon

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Karl Rosenblum Head, Global Capacity and Risk Strategy, Alcon

One of my favorite quotes by science fiction writer William Gibson is, “The future is here, it’s just unevenly distributed.” When looking across new developments in manufacturing technologies, this sentiment seems to hold truth, particularly when we consider the industry’s rate of adoption or the scope of a technology’s relevance to manufacturing companies. In spite of these elements, I predict that one thing is certain: these five areas will continue to grow, driving the evolution of the manufacturing industry:

• Advanced Analytics/Big Data
• E-Commerce
• Merging manufacturing technologies
• Robotics and automation
• Continuous bioprocessing

Advanced Analytics/Big Data

Over the past decade, multiple industries have increasingly incorporated Big Data into their business practices, leveraging the concept to improve decision-making and transform their business. When thinking about the applicability of Big Data in manufacturing, three areas start to converge:customer data, Sales &Operations Planning (S&OP) and manufacturing visibility, which I’ll address in turn.

"This is an exciting time for the manufacturing industry. It’s tempting to think of the future as far off. But, actually it is already here, 'it’s just unevenly distributed"

On the customer side, Big Data allows us to better discern and anticipate customer order patterns, allowing sales teams to tailor recommendations and production teams to predict supply and demand. This in turn, can lead to greater customer delight.

These large data sets also let companies mine S&OP data and subsequently leverage ERP systems to optimize production runs in an era where manufacturing facilities are becoming more sophisticated and automated. Big Data can also be used as a strategic tool to validate and align a company’s production and commercial business plans.

Finally, Big Data provides a continuous stream of data which can lead to optimized uptime, increased product yield and accurate, real-time feedback on product manufacturability and design. For example, at Alcon, we are leveraging advanced analytics to assemblea Quality Intelligence database, with sources ranging from customer feedback to manufacturing line performance. The database is used to find predictive trends which allow for the resolution of potential issues ahead of customer complaints.

E-Commerce

From a supply chain perspective, e-commerce finally closes the historical applications gap by moving beyond the simple process of connecting customers with products, to delivering on the benefits of new supply chain technologies. Medical device and pharmaceutical manufacturers, which typically do not interact directly with customers, have focused on growing the B2B segment, lowering costs and improving efficiency. But e-Commerce benefits are not limited to customer sales and lower costs; they include customer and company order tracking, data collection (see Big Data above) and improved customer service, which are all supportive of a positive customer experience, and customer loyalty.

Merging manufacturing technologies

Next, I will address the anticipated blending of traditionally separate technologies. Think about cars and built-in internet radio, fashion accessories and wearable tech, or in Alcon’s case, the working partnership with Verily to develop contact lenses and intraocular lenses with embedded electronics.

The drive behind the trend of merging manufacturing technologies is to support smaller, simpler products with real-time monitoring and adaptive capability. When implementing this strategy, manufacturers will see a short-term increase in costs. However, investing in merged technologies will pay off in long-term. For example, by reducing the number of separate processes that must be linked together downstream, costs and cycle time will be reduced, and throughput will increase. Finally, integrating disparate technologies can also facilitate a competitive edge, create new market opportunities and establish a company as a niche player.

Robotics and Automation

In today’s fast-paced and consumer-driven world, manufacturers must balance efficiency, high yield and low COGs with quality. As a result, manufacturing will continue to move towards higher levels of automation. However, we are at a stage where the industry cannot sustain the large lot sizes of the prior era. Automation will therefore become more flexible and capable of scaling down to manage smaller lot sizes as efficiently as larger lots. 3D printing will continue its evolution with a broader range of materials, higher quality and faster processing times. At its current rate of innovation, 3D printing is primed to potentially influence COGs, impacting the manufacturing industry as a whole.

Where tasks cannot be accomplished with traditional automation, or the product is highly dynamic, robotics will come into play more frequently. Indeed in the 2017 Gartner predictions in Supply Chain Trends and Innovations, they see that increased deployment of robots in companies will give rise to a new “c-suite” title “CRO” Chief Robotics Officer.

Continuous BioProcessing

Pharmaceutical companies have been traditionally linked to batch processes, but new developments in the area of continuous bioprocessing show that it is possible to create a product flow from raw material to finished product without the need for batch processes. While this might seem like a niche technology, it opens the door for other pharma applications, going beyond specific compounds or reaction technology. Continuous BioProcessing is also relevant for other industries, challenging the assumption that batch processing is the only way to manufacture certain products.

Conclusion

The five technologies I’ve covered are connected by a common thread—the flow and dependence on information. And even these areas are not distinct. One day your wearable tech might signal to your smartphone that you need to reorder a few items. Your smartphone will respond by sending the order to an e-commerce site which will then schedule the order via ERP and download the relevant instructions to a robotic work-cell.

This is an exciting time for the manufacturing industry. It’s tempting to think of the future as far off. But, actually it is already here, “it’s just unevenly distributed.”

 

 

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Big Data

Robotics

ERP

Supply Chain

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