Product Lifecycle Management (PLM) software can help your company keep up with the increasing complexity of developing today’s high-tech products. While smaller companies may use relatively simple Product Data Management (PDM) tools, larger companies rely on full-featured PLM systems that help automate processes and share data across global supply chains. Mid-size companies can feel stuck because PDM is too basic, but PLM feels out of reach.
This resource will help you:
• Recognize why “simple” solutions fall short and do not support your capabilities
• Better connect to customers and the supply chain
• Drive higher product development speed
• Get started with the right PLM solution
Midsize manufacturers need a system that quickly delivers the core capabilities they need to streamline product development but also gives them room to grow value over time. So, what’s the right size PLM to fit a midsized high-tech company? Download this resource and take a look.
Obtaining a first-mover competitive advantage or faster time-to-market requires a new wave in analytics. Dassault Systèmes remains a leading innovator in Product Lifecycle Management (PLM) and has invested heavily in analytical technologies to further drive business benefits for its customers in the related areas of planning, simulation, insight and optimization.
This white paper examines the challenges peculiar to PLM and why Dassault Systèmes’ EXALEAD offers the most appropriate solution. It also clearly positions EXALEAD PLM Analytics alongside related technologies like BI, data-warehousing and Big Data solutions.
Understand and implement PLM Analytics to access actionable information, support accurate decision-making, and drive performance.
Project management relies primarily on past performance to predict future results, however many companies still lack forward-looking capabilities to predict project outcomes and ensure success. Enhancing project management with PLM analytics offers the opportunity to switch from task-based activities to performance-driven ones to improve success rates.
Use PLM Analytics to:
• Gain actionable insight and valuable intelligence
• Dramatically boost business value and improve project management performance
• Reduce error-prone behavior like manual data collection
• Leverage big-data capabilities and project intelligence
Learn how to extend the value of your PLM investment and improve business performance for your company.
Midsize Aerospace and Aviation manufacturers need to choose a system that quickly delivers the core capabilities they need to streamline product development but also gives them room to grow value over time.
Product Lifecycle Management (PLM) software can help. It drives better product development performance by managing product-related data, processes and projects. While smaller companies may be able to control, access and share product data with relatively simple Product Data Management (PDM) tools, larger manufacturers rely on full featured PLM systems that help automate processes and share data across global Aerospace and Aviation companies.
Industrial Equipment Manufacturers have to connect closely with customers and introduce new products quickly and efficiently to meet their needs. While smaller Industrial Equipment Manufacturers may be able to control, access, and share product data with relatively simple Product Data Management (PDM) tools, larger Industrial Equipment Manufacturers rely on full-featured PLM systems that help automate processes and share data across global supply chains.
Industrial Equipment Manufacturer companies may find themselves in-between because:
• Product and organizational complexity drive them beyond basic PDM capabilities
• A full-featured PLM implementation may feel out of reach
They need to choose a system that quickly delivers the core capabilities they need to streamline product development but also gives them room to grow value over time. What’s the right size PLM to fit an Industrial Equipment Manufacturer? Let’s take a look.
With A&D products containing tens of thousands of parts, and potentially millions of lines of software code–produced by hundreds of companies dispersed across the globe, Aerospace & Defense organizations understand the fundamental value and dire need for robust Change & Configuration Management (CM) processes. But it’s not just the number of parts, lines of code, or partners driving the need for better processes. The complexity of products and development processes, as well as the globalization of product development, are all contributing to an environment that is becoming more difficult to manage with each new program or project.
Electronics and Software Engineering are quickly merging with traditional Mechanical Engineering to create a new paradigm in auto manufacturing: Mechatronics. Industry experts predict that this shift will bring about profound advances in automotive product development. Unfortunately, existing IT and process infrastructures do not provide sufficient capabilities to support the new paradigm: multiple data silos, a lack of standardized processes, and integration issues on a tool level (Mechanical, Electronic, Software) continue to pose serious obstacles to development efficiency, and remain a frequent source of delays, quality issues and cost increases.
Published By: RuleStream
Published Date: Aug 21, 2009
Capturing product knowledge has proven to be very difficult and early attempts at building systems to capture and reuse knowledge have failed because they were too limited technically, required users to be able to develop computer codes (or programs) to embody knowledge rules and actions, and they did not work with common product design tools such as CAD and PDM systems.
In this paper we present three case studies using online and offline motor analysis to prevent catastrophic motor failures. The online and offline analysis in our case studies use a battery of standard electrical tests including Current Signature Analysis (CSA) and Demodulated Current Spectrum Analysis (DCSA).
Over the past 20 years, Current Signature Analysis (CSA) has become an established tool for online fault analysis of AC Induction motors. Presently, very little research has been performed using current signature analysis on DC motors. This paper is a brief introduction to online fault diagnosis of DC motors using current signature analysis.