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Open source is a tried and true method for implementing standardization and bringing disparate technologies together. It has several advantages, including the ability to handle workloads across on-premises and multiple clouds.
FREMONT, CA: While COVID-19 presented a challenge to the industry, many manufacturers have discovered innovative ways to provide value to their consumers and the greater community, frequently aided by technological advancements. Manufacturers have proved their ability to pivot, experiment with different operating models, and yet push forward amidst uncertainty, whether it's providing ventilators and PPE amid shortages or even renewing investments in new digital manufacturing designs. Here are three trends in manufacturing:
Standardization through open source
While many firms choose on-premise solutions, there has been an explosion of new technological platforms to investigate. But, as vital as it is for manufacturers to access the best-of-breed solutions, it is even more crucial that these solutions function together cohesively. Open source is a tried and true method for implementing standardization and bringing disparate technologies together. It has a number of advantages, including the ability to handle workloads across on-premises and multiple clouds and improved security, and a reduction in vendor lock-in.
Sustainability will become a renewed priority
Sustainability is a long-term trend that dominated public debate before the pandemic and will likely do so again shortly. Furthermore, governments and companies are paying more attention to and measuring sustainability issues, such as better understanding their carbon and environmental footprints.
As manufacturing floors become more automated, manufacturers will better understand how to incorporate sustainability into their activities. Prioritizing green-focused IT providers to work with and leaning deeper towards efficiently digitizing elements of the supply chain are examples of this.
Artificial intelligence and machine learning
Machine learning (ML) and artificial intelligence (AI) can bridge the gap between employees and physical machinery. AI, for example, can liberate people from monotonous tasks and automatically transfer them to stations that are far apart. More machines can be remotely monitored through dashboards and performance assessments, and quality and compliance situations can be detected around the clock.