SBS Quality Management Software vs. Cherrywork Predictive Asset Maintenance

The SBS QMS Suite is composed of five interrelated software modules designed to enhance Quality compliance efficiency. 1) The SBS Quality Database includes tools for managing CAPA and 8D corrective actions, overseeing nonconformance issues, conducting risk analyses such as FMEA and SWOT, handling various audit management needs, and ensuring Environmental Health and Safety (EHS/HSE) compliance. 2) SBS Ground Control focuses on managing employee training through a Learning Management System (LMS), offering self-paced training options, and providing document control features. 3) SBS Asset Tracking Database oversees calibrated equipment, preventive maintenance schedules, and comprehensive asset inventory management. 4) The SBS Inspection Database captures and records inspection data for incoming materials, in-process checks, and final product assessments, allowing for the generation of real-time SPC charts, development of inspection and control plans, and archiving data for future statistical evaluations. 5) The SBS Vendor Management maintains an approved vendor list (AVL), formulates vendor qualification plans, and tracks the qualification history of suppliers. Each of these modules may be purchased individually or in any combination to meet your needs. On-premise and cloud-based options are available. Free demos are available for download or contact us for a cloud-based demo.

The Cherrywork® Predictive Asset Maintenance Application is crafted to reduce, optimize, and improve costs related to asset lifecycles at every phase, spanning from initial investment planning and network setup through procurement, installation, management during operations, and eventual disposal or replacement. This cutting-edge solution is vital for pinpointing unexpected equipment failures that could threaten consumer satisfaction and the overall dependability of services. Clients expect timely notifications about planned outages, which empowers them to manage their energy consumption effectively. By utilizing this application, users can engage in proactive asset maintenance, thereby sidestepping potential penalties that might arise from unanticipated failures. It utilizes historical data from multiple sources to construct accurate and credible predictive models, which facilitate the creation of forecasts and risk assessments. Moreover, the application integrates information from online monitoring systems, weather predictions, and various non-operational factors such as operational protocols, equipment specifications, and industry benchmarks, thus providing a holistic strategy for asset upkeep. This multifaceted integration of data sources not only bolsters decision-making but also significantly enhances operational effectiveness and efficiency. As a result, organizations can achieve greater sustainability and improved performance in their asset management endeavors.