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What is SmartMaintenance?

An all-encompassing approach to monitoring and predictive analysis can significantly improve the tracking of equipment conditions while also optimizing maintenance and repair workflows. This strategy employs predictive analysis to maintain the quality of production processes and evaluate the risks associated with surpassing maximum permissible loads through thorough assessments of unit operations. By integrating predictive analysis into the evaluation of unit conditions, the likelihood of emergency shutdowns can be substantially reduced. Moreover, it is essential to assess the quality of repairs by measuring equipment performance both before and after maintenance, which fosters ongoing enhancement. The incorporation of automated controls for manual repair and maintenance activities not only enhances operational efficiency but also ensures precision in execution. In addition, predictive analysis is instrumental in making strategic decisions about maintenance and repairs, enabling informed investments in new equipment through intelligent load balancing of existing resources. The management of spare parts and consumables can be refined through smart failure predictions, promoting a proactive strategy for equipment oversight. Ultimately, this comprehensive solution lays a strong foundation for bolstering operational reliability and efficiency, paving the way for future advancements in equipment management practices. This proactive approach not only mitigates risks but also contributes to sustainable operational success.

What is MaintSmart CMMS?

You have the option to create work orders either manually, through automation, or in response to equipment demand, with the flexibility for these orders to be straightforward or intricate, complete with thorough procedures and lists of spare parts. Our CMMS solution simplifies the tracking and scheduling of preventive maintenance (PM) tasks, and it also integrates maintenance activities with reliability assessments to enhance PM task lists, allowing for adjustments in maintenance intervals based on Mean Time Between Failures (MTBF). To swiftly and effectively pinpoint issues related to equipment, personnel, and procedures, it is essential to analyze downtime through equipment Failure Analysis. This downtime data can help address specific challenges, assist maintenance managers in optimizing Overall Equipment Efficiency (OEE), and calculate equipment MTBF or Failure Rate utilizing our reliability analysis software module. Additionally, a comprehensive inventory and purchasing management system is part of the offering, along with a versatile reporting tool that enables exports to formats like Excel and HTML. Furthermore, the solution features an automated work scheduling system and an event notification feature to keep users informed.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

API Availability

Pricing Information

Pricing not provided

Pricing Information

$995.00
Priced by the concurrent user. Per unit license cost drops as more licenses are acquired. Local install, server-based, cloud, web or mobile versions.
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone
iPad
Windows

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Not specified

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Ctrl2GO Global

Company Location

Russia

Company Website

ctrl2go.solutions/en/solutions/smart-maintenance/

Company Facts

Organization Name

MaintSmart Software

Date Founded

1997

Company Location

United States

Company Website

www.maintsmart.com

Categories and Features

EAM

Not specified

Categories and Features

CMMS

Asset Tracking
Inventory Control
Mobile Access
Preventive Maintenance
Purchasing
Scheduling
Service History Tracking
Technician Management
Work Order Management

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