The smart manufacturing sector is primed for huge growth over the next few years, as industries adopt new technologies in the never-ending hunt for maximum efficiency. The global market stood at $204.95 billion in 2019, and it’s projected to reach $506.33 billion by 2027.
Especially during its early weeks, the coronavirus pandemic wreaked havoc on global supply chains, as lockdowns and restrictions stymied most international shipping, manufacturing and commercial activities. Yet, interestingly, this development has generated even more interest in smart manufacturing. Advanced automation means that factories can be operational and productive even with the reduced presence of human workers, while predictive analytics, combined with the proliferation of industrial internet-of-things (IIoT) sensors, allows factories to operate with less dependence on individual vendors of components and raw materials.
Exciting as this may seem, stakeholders must not overlook the fact that manufacturing is just a part of the entire supply chain. Any chain is only as strong as its weakest link, so manufacturing can only outpace other industries so much when it comes to advancement. Even if smart factories were able to build better quality products at a faster rate, it would all be for nothing if the chain eventually fails to get the products to customers.
The smart revolution that’s happening in manufacturing is ushering in increased automation and decreased dependence on human intervention. Several types of developments in factory technologies are making these possible.
Industrial robots are now more capable of taking over manufacturing processes that were previously handled by humans. Today’s robots are equipped with better sensors and actuators that allow them to handle even the most sensitive tasks requiring precision and with virtually no room for errors.
In pharmaceuticals, for example, robots are now tasked to handle test tubes and mix potentially hazardous and radioactive compounds such as those used to make chemotherapy drugs. Even when human intervention is required, robots can be controlled remotely, over networks, minimising the need for skilled workers to physically be on-site.
Facilities are now also adopting industrial IIoT devices which integrate with their control systems and vast networks. This allows manufacturers to both monitor and control almost all manufacturing activities remotely. The data generated by these IIoT devices also fuel predictive analytics. Using artificial intelligence (AI) and machine learning (ML), manufacturers can now better identify and solve issues on the factory floor and refine their processes accordingly.
The impact of these improvements, however, will be limited if they aren’t matched by an equally efficient supply chain. For instance, industries such as pharmaceuticals and food still battle with the problem of spoilage, and many such incidents of waste occur when the products are handed over to logistics. The biopharma sector alone loses $35 billion annually due to failures in temperature-controlled logistics.
Many factors can affect product quality in transport, including travel delays and poor packaging and handling. However, most issues aren’t effectively addressed, since the root causes aren’t properly identified as soon as they occur. Many logistics operations remain paper-based, even today, which prevents the effective gathering of timely information about packages and shipping conditions. Supply chains may also involve multiple third parties such as suppliers and service providers, creating silos that prevent valuable information from being shared transparently and for lasting solutions to be discussed.
A Deloitte report on pharma supply chain planning echoes this concern, concluding that “even as industry players recognize supply chain planning as crucial to delivering competitive advantage, their traditional approach of working in silos results in an environment where short-term supply issues often consume all the attention.”
Technology adoption in the rest of the supply chain can address many of these issues. To improve logistics, supply chains can implement condition monitoring solutions that can track individual packages and parcels. Logmore, for example, provides QR tags equipped with sensors that can log changes in temperature, humidity, ambient light, and physical shocks. These tags are small and discreet enough to be placed in individual packages and can be conveniently scanned using a mobile phone camera. The logged information is then sent to the cloud, allowing users and their partners to view the information through a web portal.
Finnish pharma wholesaler Magnum Medical uses such tags for its shipments. Through the platform, the company is able to get timely parcel-level information on all of its products, ensuring that each shipment reaches its destination both in the best condition and compliant with government regulations. The specificity and accuracy of data that these monitoring solutions offer can help pinpoint the real causes of issues, allowing stakeholders to hold responsible parties accountable and compel them to do a better job.
Aside from monitoring technologies, supply chains can also look into the integration of their systems. This can enable all parties to coordinate their activities such as the timely arrival of materials from suppliers and the shipping of products to retailers and customers. Every party can now even leverage analytics to make the supply chain become more efficient. Many inventory management systems now use AI and ML to predict potential supply issues. These systems can even automatically place orders to restock, guiding suppliers and manufacturers to meet the expected demand for specific products.
The smart revolution may be happening more rapidly in manufacturing. However, it is important for supply chains to ensure that every moving part also keeps up with digitalization. There is little value in being able to manufacture products efficiently only to fail in the handling and delivery. The whole supply chain must step up.