自动化：提高四咨询的效率和决策能力

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.

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.

Electric energy operators around the world are working to increase the reliability and cyber resiliency of their systems. This includes Enel, a global power company that manages and monitors the Italian power grid. This grid:• Serves 31 million customers• Has a net installed energy capacity exceeding 31 gigawatts• Includes more than 500 power generation plants,including hydroelectric, thermoelectric, and wind• Is managed and monitored by Enel 24/7/365• Is operated by Terna, the Italian Transmission System Operator (TSO)Enel is responsible for the availability of the grid’s underlying ICS and industrial network. It also manages Regional Control Centers and Interconnection Centers which connect with the TSO. The TSO manages the flow of energy to the grid plus controls and remotely regulates the power generation of power plants, increasing and decreasing power production as required. The complex system of interaction and cooperation between Enel and the TSO has strong security implications as well as operational and business challenges.

In-vehicle communications and entertainment system hosts high-value or sensitive applications. API libraries facilitate communication and sharing of vehicle data. These API libraries are vulnerable to reverse engineering and tampering attacks and may even result in loss of passenger safety. Attackers can inject malware that may be able to migrate to other in-car networks such as the controller-area-network (CAN) bus which links to the vehicle’s critical systems. Software provided for dealers to interface with cars through the OBD2 port is vulnerable to reverse engineering and tampering attacks. Hackers may be able to abuse these tools to inject malicious code into the ECUs and CAN bus. Attackers can lift the cryptographic keys used, and use that to build their own rogue apps/software. Their cloned version of the original app/software may have altered functionality, and may intend to gain access to other in-car networks.

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.