SuperFrio 利用 Blue Yonder 优化其冷链物流
公司规模
Large Corporate
地区
- America
国家
- Brazil
产品
- Blue Yonder’s warehouse management solution
技术栈
- Cloud-based SaaS
- Artificial Intelligence
- Machine Learning
实施规模
- Enterprise-wide Deployment
影响指标
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
技术
- 功能应用 - 仓库管理系统 (WMS)
适用功能
- 仓库和库存管理
用例
- 仓库自动化
- 库存管理
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
SuperFrio 是南美冷藏物流领域的领导者。该公司在巴西经营着 22 个配送中心，另有 5 个配送中心正在建设中。SuperFrio 的仓库运营非常复杂，22 个配送中心每月有 10,000 个库存单位、300,000 个托盘位置和 15,000 辆汽车要派送。该公司制定了雄心勃勃的增长计划，旨在标准化流程并提高质量、准确性、效率和客户响应能力。
挑战
SuperFrio 是南美冷藏物流领域的领导者，在巴西经营着 22 个配送中心，还有 5 个正在建设中。为了支持其雄心勃勃的增长计划，该公司决定用更高速度和自动化水平取代其传统的仓库软件和手动流程。目标是标准化流程并提高质量、准确性、效率和客户响应能力。SuperFrio 的仓库运营非常复杂，22 个配送中心每月有 10,000 个存储 SKU、300,000 个托盘位置和 15,000 辆车辆要调度。
解决方案
SuperFrio 于 2018 年开始在部分配送中心实施 Blue Yonder 的仓库管理解决方案。该解决方案是一种全面、高度可扩展、实时的软件即服务 (SaaS) 解决方案，可全面优化 SuperFrio 的任务管理、劳动生产率和库存流动。Blue Yonder 的仓库管理功能可实现数字环境并优化每个操作步骤，以确保准确性、效率、合规性和理想的客户服务水平。Blue Yonder 通过实施模板、简化的流程更改、更好的入职培训和快速实施来支持更快的价值实现。SuperFrio 的业务需求不断得到满足，而无需进行定制，从而避免软件升级变得痛苦且成本高昂。
运营影响
数量效益
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
相关案例.
Case Study
Hospital Inventory Management
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.
Case Study
IoT Solution for Cold Chain
Most of the customer's warehouses run on utility and generator power. Since these warehouses are in remote locations, power outages are a very common scenario. Diesel fuel, thereby, becomes a significant cost for these warehouses. Energy consumption was also very high due to the lack of a consistent temperature throughout the facility. This lack of a consistent temperature in all areas and no way to control it, resulted in the customer losing a significant amount of their temperature sensitive goods due to spoilage.
Case Study
DSV Road levels their workflow and decreases stress thanks to 4 BT Autopilots
During peaks in the workflow employeescan experience stress which makes them prone to causing damage. Avoiding these peaks also eliminates the need to hire temporary workers that require extra time and costs for education.
Case Study
Hardware Retailer Uses Data Warehouse to Track Inventory
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.
