Manufacturing businesses are increasingly adopting advanced digital technologies to enhance their capabilities to satisfy customer demand for the production of more high-quality products at a faster rate than ever before,
Automation, for example, is employed in several applications including assembly lines, computer-aided design and manufacturing (CAD/CAM), and ‘just in time’ delivery of inventory, where demand for raw materials is tied to accurate forecasting of customer requirements.
Most recently, we’ve seen the advent of the smart factory, in which increasingly connected machines, devices, sensors and people are delivering greater efficiency and productivity. Indeed, the manufacturing industry reported an 84 percent increase in IoT network connections in 2017, more than any other sector.
What’s more, a recent industry report reveals how the majority of senior industrial executives believe the data generated by connected machines and people will inform their decision-making and reduce costs, with a further 86 percent stating that their manufacturing business would be able to serve its customers more effectively through the combined use of digital technologies and data analysis.
So many areas of the manufacturing process are now digitized and connected; we indeed are in the midst of the Fourth Industrial Revolution. However, as the number of connections continues to grow, so too will the number of attendant risks. While the potential benefits are clear, it’s therefore likely that we’ll also see a dramatic increase in the disruption of the technology itself.
Maintaining communication in a smart factory
The central nervous system of a smart factory is made up of a network of machine-to-machine communications, automation technologies, and connected IoT devices and sensors, all of which are dependent on reliable, consistent connectivity.
Its performance requires information to be constantly and continuously available through bi-directional communication over both wired and wireless networks, bringing together sensors, robots, and employees with scanners, mobile devices and workstations. Any degradation or failure in this communication could have a negative effect on the factory floor which, in turn, could impact efficiency, production and, ultimately the manufacturer’s bottom line.
With the potential for delays or disruptions to a manufacturer’s production line or processes to put its revenue, just-in-time delivery, safety, and customer service at risk, service assurance within its IT environment is paramount.
Visibility into a complex network
Traditional network monitoring and assurance tools may no longer be enough, however, to provide companies with the window they need on this new environment.
Pervasive, end-to-end visibility into the entire IT infrastructure is critical, as it enables manufacturers to pinpoint the cause of a performance degradation, wherever it’s located along the service delivery path and quickly resolve any issues – after all, you can’t fix what you can’t see.
Manufacturers should then utilize a smart data approach, in which advanced analytics extract the important information from the wire data that traverses the network, in real time. Prepared and optimized at the point of collection, this smart data is ready and analyzed for views that include rich detail related to Key Performance Indicators (KPIs), errors, and metrics. This provides the IT staff within a manufacturer with the actionable intelligence they need to identify issues as quickly as possible, and to maintain their infrastructure at the level necessary to meet customer demand.
Vital to transformation
Digital transformation is key to the success of manufacturing businesses in an increasingly competitive market, and service assurance is vital to achieving that transformation.
By way of illustration, consider the issues experienced by a multinational beverage producer and distributor about the Enterprise Resource Planning system it used for just-in-time-delivery of products. These performance problems were impacting its customer service and revenue opportunities, and ultimately risked tarnishing the company’s reputation. It was taking customer service representatives between eight and nine minutes to enter a customer order into a system when it should normally have taken only one minute. It was not uncommon for the system to freeze multiple times during a single transaction and the customer service representatives found themselves making small talk each time this occurred. Not only did this risk damaging the brand’s name, but it also impacted the total number of orders that could be taken on any given day, which affected overall revenue. This was clearly a critical problem that needed to be addressed.
Issues such as these are the most challenging to resolve, however. When the communications path can include a SaaS application or private cloud-based application, multiple data centers, call centers, and manufacturing plants, all connected over third-party wide area connections, it is easy to see how hard it may be to pinpoint the source of the disruption. Revenue, customer service, and employee productivity all depend on organizations having rich, vendor-independent visibility across these complex environments.
As manufacturers become increasingly connected, and take advantage of more streamlined, autonomous processes, IT teams will become ever more dependent on end-to-end visibility and actionable intelligence to avoid costly performance degradation and outages. It’s here, then, that a smart data approach to service assurance will prove invaluable.
