While reducing Unscheduled Downtime is a major reason plants consider industrial analytics solutions, many factories don't have the full picture when it comes to calculating the total cost of these unforeseen events. The range of costs associated with machine breakdowns is a crucial aspect of ROI.
Digitalization journeys always start with more unknowns than knowns. Though spending is rightfully down, abandoning all IIoT projects leaves you unprepared for the day after the pandemic. Instead, evaluate which projects provide the most value and which vendors have the capital to weather the storm.
The leap from conceptualizing to actualizing a Maintenance 4.0 strategy can be difficult. The Maintenance 4.0 Handbook provides step-by-step guidance for driving maintenance initiatives from pilot to scale, and demonstrates how to target different stakeholders to propel cross-plant buy-in.
Pulp and Paper is already a highly automated industry that grasps the potential of technology. While reactive maintenance will continue to play a role in O&M, incorporating AI-driven Industrial Analytics into the Pulp and Paper maintenance playbook offers significant new cost savings possibilities.
The right moment to access your asset data is right now. Prioritizing Big Data insights for your plant can significantly reduce unscheduled downtime while increasing data health visibility across the plant. Operationalizing data empowers plants to make smarter, safer O&M decisions.
The scarcity of data scientists renders certain predictive maintenance (PdM) solutions costly or impractical. By automating repetitive machine learning tasks, PdM products based on Automated Machine Learning offer a highly scalable, more accurate, and results-oriented approach to industrial analytics.