Boise Cascade Scales AssetWatch Across the Enterprise

Boise Cascade operates a network of manufacturing facilities across the United States producing engineered wood products. Prior to deploying AssetWatch, maintenance practices varied significantly from site to site. Each facility had its own processes, tools, and levels of experience. While some sites had maintenance programs in place, much of the organization relied on reactive maintenance, aging assets, and limited condition-based monitoring (CBM) experience. Collaboration between facilities was minimal, and data-driven insights into asset health were difficult to standardize or scale.

Several members of the Boise Cascade team recognized the potential value of predictive maintenance technology. To evaluate its impact, two facilities independently piloted AssetWatch, meeting regularly to compare results, lessons learned, and early successes. Those pilots quickly demonstrated that predictive maintenance could reduce unplanned downtime and provide actionable insights.

However, scaling the solution across an enterprise with diverse teams, experience levels, and priorities presented a new challenge. The rollout would require not only technology, but also change management, training, and a consistent approach that could work across all facilities.

Boise Cascade selected AssetWatch to support an enterprise-wide rollout of predictive maintenance across its manufacturing operations. Key decision factors included cost-effective pricing, reliable hardware and data quality, dedicated Condition Monitoring Engineer (CME) support, and a proven ability to help organizations with limited prior CBM experience.

AssetWatch provided a fully managed predictive maintenance program, combining wireless vibration monitoring, with a dedicated team of U.S.-based vibration experts, providing ongoing support and training to help Boise Cascade move from reactive maintenance toward a standardized, data-driven approach.

After confirming value at the pilot sites, leadership expanded the program across the enterprise. Over a 13-month period (November 2023 – December 2024), the program scaled from 1 to 17 manufacturing sites and from 96 to 1,224 monitored measurement points, creating a consistent predictive maintenance standard across the organization.

A major focus was education, collaboration, and adoption. For many teams, AssetWatch represented a new way of working. The AssetWatch CME team played a critical role by:

• Educating teams on how predictive maintenance supports day-to-day maintenance decisions
• Using real sensor data to demonstrate actionable insights to both leadership and frontline teams
• Providing flexible training schedules to accommodate plant operations
• Connecting teams across facilities to share success stories and best practices

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Training and onboarding were tailored to each facility. AssetWatch worked closely with plant managers and maintenance leaders to identify critical assets, define roles and responsibilities, and deliver plant-specific training. As early wins accumulated, engagement grew, and facilities began sharing results internally, accelerating adoption across the enterprise.