Manufacturing

Manufacturers need AI Cloud to address consumer demands, optimize operations and keep their employees safe

Manufacturers are facing unprecedented challenges on a global scale. Supply chain disruptions, shipping bottlenecks, sustainability concerns, and maintenance backlogs are further compounded by a rapidly evolving landscape of high consumer expectations and increased operational complexity. Manufacturers need to find new ways to solve some of their most important issues.

Discover more AI use cases for Manufacturing

• Supply Chain Disruptions

  Supply chain disruptions are expected to become more common. According to the Economist Intelligence Unit, 54 percent of executives say that organizations must make significant changes in order to effectively manage supply chain disruptions in the next five years

• Sustainability

  Sustainable operations are no longer optional. Companies could face up to $120 billion in increased costs from environmental risks in their supply chains within five years. And failure to meet targets can jeopardize customer loyalty and market opportunities (CDP).

• Quality and Defects

  Defective materials reduce efficiency and increase the cost of manufacturing. They generate waste, lead to downtime, and require resource-intensive quality assurance and remediation. For example, an aerospace giant recently estimated that manufacturing quality defects will cost the company $1 billion (Seattle Times).

• Downtime

  Unplanned downtime costs industrial manufacturers an estimated $50 billion annually. Equipment failure is the cause of 42 percent of this downtime, with unplanned outages resulting in excessive maintenance, repair, and equipment replacement (IndustryWeek).