Elsevier Enhances Order Fulfillment with Voxware's Voice Solution
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Voxware VoiceLogistics Solution
- LXE Mobile Computers
- Metrologic Scanners
Tech Stack
- VoiceXML
- Internet Protocols
- Wearable Technology
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Employee Satisfaction
- Customer Satisfaction
Technology Category
- Functional Applications - Warehouse Management Systems (WMS)
- Functional Applications - Remote Monitoring & Control Systems
- Analytics & Modeling - Real Time Analytics
Applicable Functions
- Warehouse & Inventory Management
- Logistics & Transportation
Use Cases
- Inventory Management
- Warehouse Automation
- Predictive Maintenance
Services
- System Integration
- Training
About The Customer
Elsevier is a leading publisher of Health Science and Technology Information, operating over 85 locations worldwide. The Linn, Missouri location is responsible for processing 100,000 orders annually. Elsevier's end customers include researchers, students, educators, and practitioners globally. To ensure accurate and timely order fulfillment, Elsevier implemented Voxware’s voice solution to enhance their operational efficiency and accuracy.
The Challenge
Previously, Elsevier's Linn, Missouri location was fulfilling orders using RF scanning, which had several drawbacks. The RF guns sometimes had difficulties reading labels printed on cardboard, leading to inefficiencies and errors. Workers were slowed down by the cumbersome RF units, which they had to juggle along with the products during order picking. This not only risked damaging the RF units but also made the process less efficient. Additionally, there was very little insight into productivity rates and picking errors, making it difficult for management to track and improve operations.
The Solution
Elsevier implemented Voxware’s VoiceLogistics Solution, which included mobile computers from LXE and scanners from Metrologic. The voice-driven picking system allowed workers to keep their hands free while fulfilling orders, significantly improving efficiency. The system is speaker-dependent, with a 99.9% recognition rate, ensuring high accuracy. Workers are directed through the warehouse via voice prompts that sync with the WMS in real-time. This paper-free system allows workers to voice in product codes and quantities, providing real-time updates to management. The solution also offered flexibility and compatibility with Elsevier's highly customized WMS system from Boss.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Aircraft Predictive Maintenance and Workflow Optimization
First, aircraft manufacturer have trouble monitoring the health of aircraft systems with health prognostics and deliver predictive maintenance insights. Second, aircraft manufacturer wants a solution that can provide an in-context advisory and align job assignments to match technician experience and expertise.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
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.
