Quad/Graphics Partners with Westfalia Technologies for Lomira Storage Project
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- High Density Storage System
- Storage Retrieval Machines (SRMs)
- Conveyor Systems
Tech Stack
- Automated Storage and Retrieval Systems (AS/RS)
- Warehouse Management Systems (WMS)
- Robotic Palletizing Systems
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Customer Satisfaction
- Cost Savings
Technology Category
- Functional Applications - Warehouse Management Systems (WMS)
- Automation & Control - Automation & Process Control Systems
Applicable Functions
- Warehouse & Inventory Management
- Logistics & Transportation
Use Cases
- Warehouse Automation
- Inventory Management
- Predictive Maintenance
Services
- System Integration
- Hardware Design & Engineering Services
- Software Design & Engineering Services
About The Customer
Quad/Graphics is a leading commercial printing company based in Wisconsin, USA. It is the largest privately held commercial printer in the world, known for its high-quality printing services. The company operates multiple facilities and serves a diverse range of clients, including publishers, catalogers, and retailers. Quad/Graphics is committed to innovation and efficiency, continually seeking ways to improve its production processes and meet the evolving needs of its customers. The Lomira facility, one of its key locations, plays a crucial role in the company's operations, handling a significant volume of printing and storage tasks.
The Challenge
Quad/Graphics, the largest privately held commercial printer in the world, faced a significant challenge in optimizing its storage and retrieval processes at its Lomira, Wisconsin facility. The facility needed to store three different styles of pallets—plastic USPS, plastic 9-block, and a wooden internal pallet—without the need for slave pallets. The existing storage system was not efficient enough to handle the high volume and variety of pallets, leading to delays and inefficiencies in production. The company required a solution that could streamline and expedite production by making work-in-process more readily accessible. Additionally, the solution needed to be scalable and flexible to meet the company's long-term needs.
The Solution
Quad/Graphics partnered with Westfalia Technologies to design, construct, and install a high-density automated storage system at its Lomira facility. The new system features 42,005 pallet positions and measures 776 feet long, 92 feet wide, and 107 feet high. It includes four storage retrieval machines (SRMs) and 1,600 linear feet of conveyors. The system is designed to store three different styles of pallets without the need for slave pallets. Two SRMs are installed in each aisle, effectively cutting the travel distance of the cranes in half. This design, coupled with center-stationed in-feed and out-feed conveyors, ensures extremely high throughput rates. The high-density storage system is expected to streamline and expedite production by making work-in-process more readily accessible. Westfalia Technologies, known for its quality, flexibility, and dependability, has installed similar systems worldwide, making them a trusted partner for this project.
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.