Since January 2020, when WHO declared the COVID-19 pandemic as a world health emergency, all countries faced many challenges in different levels. Economically, the world is experiencing about 5% contraction in 2020, and in the best scenario with no rise of the second wave, the economy could possibly contract by 5.4% by end of 2021, 6.5% less than pre COVID-19 prediction according to IMF.
From the industry perspective and as of July 2020, the world manufacturing contracted by 2.7 PM Index, the US contracted by 0.5 and Euro zones by 2.6 while China grew by 1.2 PM Index.
Manufacturing is one of the most important elements of economy which globally contributed 16% to global GDP in 2018. For example, the US manufacturing in 2019, by contributing 11.6% to GDP is the 8th largest economy of the world and conducts 63% of R&D of all private sectors and is driving more innovations than any other sector.
The major impacts of COVID-19 on the manufacturing can be summarized as:
1- Supply chain disruption:
This is driving the deglobalization of supply chain and making manufacturer to demand real time visibility over end-to-end of supply chain.
2- Lockdown:
In the US, every day of shutdown costs $25 billion in lost output, New Product Introduction (NPI) has been delayed and revenue and profit has sharply come down.
3- Sharp decline in demand:
Given the situation of the economy and unemployment, consumer spending and therefore demand is declining sharp
4- Low liquidity and cash flow:
Driving all manufacturer to reduce cost and employees, and put a stop on existing and future projects, and look for government bailouts. This is also causing manufacturer to realize the importance of productivity, efficiency and flexibility of their manufacturing and production line in order to be able to produce high demand products in the market such as COVID-19 Personal Protective Equipment (PPE) and ventilators.
5- Reopening and New-Norm:
Social distancing has a direct impact on the number of workforces on the plant floor, causing up to 40% to 50% reduction, which makes the scheduling and maintaining of production capacity challenging.
6- Safe plant/workplace:
Another challenge is to create a safe and healthy manufacturing plant for workers during the pandemic and prevent possible rise of second wave and continuation of shutdown.
This being said, as far as manufacturing technologies and more specifically smart factory, digital transformation and IIoT, there are strong indications that the current decrease in demand will be just a short-term effect. In the medium-to-long run, the COVID-19 manufacturing technology impact seems to be extremely positive.
Studies show that 66% of international and 70% of DACH manufacturing executives believe that in the coming months, digital transformation will accelerate and additional investment in its infrastructure will take place.
As the result of “new norm” culture and in order to build resilience, manufacturer will adopt manufacturing process and operation efficiency, labor productivity, production flexibility, automation and remote operation in a faster pace.
But the question is: what technologies and solutions will be in high demand and how they will be helping manufacturing during and post covid-19 pandemic:
• Production end-to-end visibility and digital performance management
From machine connectivity to IIoT and Manufacturing Execution System (MES), many Smart Factory tools make this possible for manufacturer. Remember that the more digitized manufacturing is, the easier it is to have visibility over operations and production. For example, during COVID-19 many manufacturers are deploying Lite MES solution in shorter period of time with less cost to optimize production, increase transparency and reduce the waist.
• Vision-based control and QC systems
Image processing systems and IIoT devices come to place not only to help on the safety of the workplace and workforce by detecting fevers, but also help on the visual quality control of the products and processes and predict line behavior.
• Remote operation, asset control and predictive maintenance
Asset connectivity, IIoT and cloud-based control software can provide the capability of monitoring and controlling equipment remotely. With implementation of AI and data analysis services in the cloud, one can also achieve intelligent predictive maintenance and achieve a minimum of 10 to 40 percent reduction in field-service costs and downtime.
• Track and trace, real time location system, indoor autonomy
Innovative technologies such as Li-Fi location system can provide real time millimeter accuracy of navigation and positioning for indoor autonomous vehicles such as robots, drones and lift trucks. In addition to Li-Fi, 5G and smart wristbands can provide personnel track and tracing and physical distancing capabilities as required by the new norm.
• Cybersecurity
As manufacturing increasingly digitize the operations, cybersecurity comes to the center of attention. Statistics from various sources show that cyberattacks are on the rise during Covid-19 and 71% security professionals have noticed an increase in security threats or attacks. One of the AI-based security solutions is machine learning-enabled anomaly detection for threat detection, whereby algorithms constantly run through IIoT device traffic data to detect abnormal behavior
• Efficiency and productivity
Technologies such as IIoT and manufacturing performance monitoring applications can increase production efficiency of entire production lines and labor productivity by using advanced analytics to optimize process parameters. The algorithm analyzes information on all available variables, including production, scheduling, asset condition, and input goods. With the help of Digital Twins and AI, this optimization process can be automated with no interruption and downtime for the line.
• Overall Equipment Effectiveness
With monitoring applications, IIoT and advanced data analytics, root causes can be identified, and countermeasures can be planned on availability, performance, and quality.
• Supply Chain
Due to Covid-19, manufacturing has been affected by production, shipping, and distribution disruption or delay as well as demand variability. Digital twins can be used to create digital representations of the end-to-end supply chain that enables customers to explore dynamic sourcing options, assess risks and evaluate trade-offs to speed or automate decisions. By combining Digital Twins and AI, manufacturers can develop resilient long-term risk management plans and engineer low risk supply chains.
