Download PDF
SimData Manager: Centralizing and Standardizing CAE Data for Global Collaboration
Technology Category
- Application Infrastructure & Middleware - Database Management & Storage
- Infrastructure as a Service (IaaS) - Cloud Databases
Applicable Industries
- Retail
Use Cases
- In-process Traceability
- Supply Chain Visibility
Services
- System Integration
The Challenge
The case study highlights three main challenges faced by companies in managing their Computer-Aided Engineering (CAE) data. The first challenge is the need for a central location where all CAE users can manage their data within an enterprise for easy retrieval and full traceability from CAD to CAE, and all versions of CAE to the final report. The second challenge is the lack of standardization in methods used by different engineers, the loss of knowledge when employees leave, and the manual nature of the processes. The third challenge is the difficulty in tracking versions of CAD and CAE models and distributing project data globally, especially for companies with multiple development organizations in different geographic locations.
About The Customer
The customer in this case study is any company that uses Computer-Aided Engineering (CAE) in their operations. These companies often have multiple engineers working on different projects, and they need a way to manage their CAE data efficiently. They may have development organizations in different geographic locations, making it difficult to track versions of CAD and CAE models and distribute project data globally. They also face challenges in standardizing methods, retaining knowledge when employees leave, and automating their processes.
The Solution
The solution to these challenges is the SimData Manager, a simulation data management software by PDTec. The software stores all CAE data centrally in a database and provides full traceability via an audit trail, addressing the first challenge. To tackle the second challenge, SimData Manager supports method standardization, captures all knowledge in the company, and automates the process which can be built interactively in the system. For the third challenge, SimData Manager provides a versioning system for CAE-related data and allows access via a web client, enabling global teams to work closer together on joint projects and provide all project team members access to them.
Operational Impact
Related Case Studies.
Case Study
Improving Production Line Efficiency with Ethernet Micro RTU Controller
Moxa was asked to provide a connectivity solution for one of the world's leading cosmetics companies. This multinational corporation, with retail presence in 130 countries, 23 global braches, and over 66,000 employees, sought to improve the efficiency of their production process by migrating from manual monitoring to an automatic productivity monitoring system. The production line was being monitored by ABB Real-TPI, a factory information system that offers data collection and analysis to improve plant efficiency. Due to software limitations, the customer needed an OPC server and a corresponding I/O solution to collect data from additional sensor devices for the Real-TPI system. The goal is to enable the factory information system to more thoroughly collect data from every corner of the production line. This will improve its ability to measure Overall Equipment Effectiveness (OEE) and translate into increased production efficiencies. System Requirements • Instant status updates while still consuming minimal bandwidth to relieve strain on limited factory networks • Interoperable with ABB Real-TPI • Small form factor appropriate for deployment where space is scarce • Remote software management and configuration to simplify operations
Case Study
How Sirqul’s IoT Platform is Crafting Carrefour’s New In-Store Experiences
Carrefour Taiwan’s goal is to be completely digital by end of 2018. Out-dated manual methods for analysis and assumptions limited Carrefour’s ability to change the customer experience and were void of real-time decision-making capabilities. Rather than relying solely on sales data, assumptions, and disparate systems, Carrefour Taiwan’s CEO led an initiative to find a connected IoT solution that could give the team the ability to make real-time changes and more informed decisions. Prior to implementing, Carrefour struggled to address their conversion rates and did not have the proper insights into the customer decision-making process nor how to make an immediate impact without losing customer confidence.
Case Study
Digital Retail Security Solutions
Sennco wanted to help its retail customers increase sales and profits by developing an innovative alarm system as opposed to conventional connected alarms that are permanently tethered to display products. These traditional security systems were cumbersome and intrusive to the customer shopping experience. Additionally, they provided no useful data or analytics.
Case Study
Ensures Cold Milk in Your Supermarket
As of 2014, AK-Centralen has over 1,500 Danish supermarkets equipped, and utilizes 16 operators, and is open 24 hours a day, 365 days a year. AK-Centralen needed the ability to monitor the cooling alarms from around the country, 24 hours a day, 365 days a year. Each and every time the door to a milk cooler or a freezer does not close properly, an alarm goes off on a computer screen in a control building in southwestern Odense. This type of alarm will go off approximately 140,000 times per year, equating to roughly 400 alarms in a 24-hour period. Should an alarm go off, then there is only a limited amount of time to act before dairy products or frozen pizza must be disposed of, and this type of waste can quickly start to cost a supermarket a great deal of money.
Case Study
Supermarket Energy Savings
The client had previously deployed a one-meter-per-store monitoring program. Given the manner in which energy consumption changes with external temperature, hour of the day, day of week and month of year, a single meter solution lacked the ability to detect the difference between a true problem and a changing store environment. Most importantly, a single meter solution could never identify root cause of energy consumption changes. This approach never reduced the number of truck-rolls or man-hours required to find and resolve issues.