The spiking chart you see here shows the volume of remote activity on the Sight Machine platform. It’s a pretty impressive increase over a very short period of time. As I’m sure you guessed, this was driven by the Covid crisis as factories around the world sent home everyone who did not need to be on site. Manufacturing and operations executives now must be able to access and visualize critical data about their plant operations remotely – anytime, anywhere.
Make no mistake – the unfolding Covid crisis has had a significant impact on manufacturing operations globally. In industries that produce products essential to global economies – food, chemicals, packaging, medical supplies, fuel – the problem of running safe operations is challenging. The decrease in global demand combined with fears of the virus spreading among teams of workers has shuttered non-essential factories. Many are starting to slowly re-open, but with big caveats and under the likelihood that COVID outbreaks may interrupt business again in coming months.
COVID Chapter 2: Constant Interruptions
What happens next? We are quickly finding out. In China, the Wuhan region where, ironically, much of the n95 mask production is clustered, is back up and running but many restrictions on social distancing remain. After a period of relative calm, Singapore just locked down when new hot spots emerged. Spain and Italy are lighting their factory lines and restarting production. In the U.S., some parts of the country are already trying to open back up. Large manufacturers are starting plans to call back their workforces. That said, everyone is cautious about work environments where people spend a lot of time indoors together in close quarters. Unfortunately, this describes many manufacturing operations today.
Going forward, manufacturing and operations leaders will need to focus energy on creating a safe working environment. This will be non-negotiable. Governments and workers will demand it. Reputation risks will enforce it. Organizations will need to think of novel strategies to enable this new normal. The silver lining? This challenge and disruption can help them reinvent operating models to make them more resilient and make their plants more efficient.
Safer, More Efficient Manufacturing Through Remote Operations
With the advent of streaming data technologies that provide access to machine level data in an easy to use form, a number of functions at manufacturing plants that have historically been deemed essential to be co-located with the shop floor could potentially be reimagined as remote functions in future.
Some examples of manufacturing functions that have always been on premise but could be switched to remote
- Production planners/schedulers: Historically they were supposed to be next to production lines but could use digital platforms for shop floor scheduling
- Engineers: CI and process engineers have historically root-caused problems based on in-person observations. This could be moved to remote work when they gain holistic access to the variables they need to track, while maintaining a more skeleton crew in the factory or plant
- Maintenance work order processors: They have always been on site to date there is no reason they could not be fully remote. The only technicians who need to be on site are those who will actually on the ground fix and maintain machines
To empower these roles for full remote operations, a manufacturing facility must be digitally enabled. This means real time access to shop floor machine data in a usable contextualized form. It is a big improvement over supply and demand data, which is all that manufacturers have had access to up until recently.
Real time streaming data technologies such as Sight Machine make this possible by providing a unified data model for manufacturing operations and a set of visualization and analytical tools that can make the idea of remote manufacturing operations a reality.
A Remote Manufacturing Operations Model for Shared Services
Businesses across many sectors have built a competitive advantage by leveraging a central shared service model. We all know about shared IT service models – specialized internal organizations that handle all the IT tasks across the units of companies. Other shared services models include , marketing (shared graphic design and video capabilities), HR, Finance and more. In manufacturing, for cultural reasons and also due to the technology challenges, the shared service operations model has not yet taken hold. Manufacturing operations shared service teams struggled to combine shop floor data with other enterprise data in real time, and create the necessary holistic and fully integrated system-level view of one or more plants.
We are seeing this shift with our customers as an outgrowth of the move to remote operations. First, they are leveraging the virtual dashboards and our new visualization capabilities to put all the metrics required for remote monitoring in a single location. The dashboards are now being used more than ever and by a wider span of titles and roles across the organization to keep everyone on the same page. Second, process engineers are now actively and effectively using our platform for remote root cause problem solving.
Getting Everyone On the Same Platform
This is the first step towards realizing a manufacturing shared services model. And it’s good. Because models should emerge from behavior that teams exhibit rather than top-down initiatives. This is, however, only the first step. Right now, in most cases, all efforts around using manufacturing data are focused only on optimizing individual factory operations by people from the same factory.
Few operations teams are thinking about optimizing across a network of factories. Planning, process and maintenance remain largely local activities. On-site will always be a big part of any process. But learnings and optimizations can be easily shared across plants. The core work around these efforts can be centralized and digitized. Once a manufacturing operation attains that level, this unlocks a whole new layer of questions: more specifically, how do we optimize the manufacturing network rather than the plant? And how do we define a cross functional combined local and remote working model to accelerate deployment of truly advanced analytics techniques? For example, the power of Artificial Intelligence and Machine Learning is magnified when models and learning can be built upon larger pools of relevant data.
Towards A Future Remote Manufacturing Operations Model
Having spoken about a remote future for manufacturing operations, I want to be clear that manufacturing will always require a physical presence onsite. Even the most automated plants need people to come onsite to break fix. And no one wants to lose the in-person chemistry and camaraderie that healthy manufacturing teams enjoy. That said, many manufacturing operations are feeling the acute pains of stretched supply chains and problems making what the world needs. Creating a more resilient, sustainable supply chain and manufacturing base will help us move towards a more resilient society and a stronger manufacturing base. Centralizing key operational capabilities with the help of technology can yield outsized manufacturing gains, and quickly. We are already heading in the right direction and the external pressures manufacturing is feeling to create safer, remote capabilities, while challenging, are paving the way.
