Aravo Solutions 为富达国际的全球第三方风险和绩效计划提供支持

The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.

SML Intelligent Inventory's customers, some retail and supply chain businesses wanted a cost-efficient way to improve their inventory management so that they can increase their revenue.

Emerson wanted to provide a connected environmental analyzer to their customers. They wanted to leverage IoT technologies to provide a software solution that was easy to use, real-time and centralized. Compliance with pollution control board guidelines and the ability to remotely calibrate and troubleshoot these devices was the primary objective. Requirements - Centralized Remote Monitoring. - IoT Based Smart Environmental Analyzers. - Remote Calibration and Troubleshooting. - User Friendly Application. - Reporting & Dashboards. - Compliance with pollution control board guidelines.

Top ABB customers asked for advanced services and faster parts replacement to keep their plants up and running, where production downtime can cost up to $2 million per minute.

Pharmaceutical production is subject to a strict set of enforced rules that must be adhered to and compliance to these standards is critically necessary. Due to the efforts of WIN 911’s strategic partner Micromedia, Lilly was able to adopt an alarm notification infrastructure that integrated smoothly with their existing workflows and emergency hardware and protocols. These raw energy sources enable the industrial process to function: electricity, WIN-911 Software | 4020 South Industrial Drive, Suite 120 | Austin, TX 78744 USA industrial steam, iced water, air mixtures of varying quality. Refrigeration towers, boilers and wastewater are monitored by ALERT. Eli Lilly identified 15000 potential variables, but limitations compelled them to chisel the variable list down to 300. This allowed all major alarms to be covered including pressure, discharge, quantity of waste water discharged,temperature, carbon dioxide content, oxygen & sulphur content, and the water’s pH.

Ace tracked which products retailers ordered, when they were ordered and shipped. However, the company could not track or forecast actual sales. Data used for reporting was up to a one-week old, owing to performance and data cleansing issues. Requirement to integrate wholesale and inventory data with POS data to help drive key business decisions, improve category management, lower inventory costs and optimize pricing. Reliance on custom coding to integrate POS data was excessively resource intensive and led to major performance constraints.