Why cloud PLM solutions are taking businesses by storm

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With today’s increasing remote-centric work culture, the ability to enable teams and partners to collaborate via cloud solutions is essential to ensure productivity.

To improve efficiency, shorten time to market, and reduce the cost of investment, industries are taking initiatives to move their manufacturing and operations from traditional methods to digital manufacturing by adopting new emerging technologies and Industry 4.0 strategies.

Product lifecycle management (PLM), where all the product data is stored, managed, and exchanged with an ecosystem, is the backbone of digital manufacturing. Managing PLM instances efficiently is a vital need for every organization. Typical PLM implementation, with over 500 users having to configure industry-standard processes with integration with ecosystems, takes around a year to gather requirements, build, and launch for production. For clients, this is a year of major investment in high-class servers for integration to carry out system integration testing, quality test servers, and most importantly, production servers. As an enterprise application, PLM needs at least four to five different high-end servers to configure seamless software for the required business needs.

In a recent scenario, one of the automotive leader from APAC wanted to do a quick launch of Teamcenter application for their vehicle program management. Post project kick-off the client realized that they have to wait for a minimum of six to eight weeks to receive the high-end servers after going through the formal procurement process. This inevitably affects project plans.

Capgemini’s PLM experts understand this problem. To avoid high investment at the beginning and have readily available servers, we propose a cloud deployment option. This applies to all PLM applications. Our PLM team has developed cloud deployment accelerators and successfully tested on popular cloud platforms like Amazon AWS, Microsoft Azure, and IBM cloud. For this blog, we will focus on the Siemens Teamcenter PLM, which is being tested and successfully hosted on Amazon Cloud. Amazon’s server management terminal is easy to use and can configure the high-end server within 30 minutes to make it available for Teamcenter installation. Multiple servers can be built with the desired CPU, memory, and operating system. To save costs, servers can be taken down with the operating system’s normal shut-down button when they are not being used. Data security is always an issue for cloud deployment, but Amazon Web Services (AWS) provides a more reliable security measure that’s guaranteed to keep the data safe and secure.

To ensure ROI, the client should use the PLM for at least three to five years. During this time, additional enhancements such as business group/departments, and users get onboarded onto the PLM platform to manage their business processes. AWS scalability is a key feature that helps increase CPU, RAM, and secondary storage without having any impact on the installed software. This allows organizations to pay only for the required hardware and gradually increase capacity based on need.

Business keeps evolving, hence users frequently require PLM AM (application maintenance + application development) teams to configure them into PLM. The servers have to be arranged for use by different project teams for continuous development and continuous deployment. Arranging and installing these machines, and configuring PLM and its required software for development takes one to two weeks of work by both intra and IT teams. Whereas, AWS has a server replication feature that helps to create replicas of the existing configured servers. The time required to configure such a server ranges between 20 minutes and one hour, hence it is possible to have a fully baked, ready-to-use system in little time.

While there are many advantages of cloud-based PLM, there are also a few concerns or limitations that need to be taken into consideration when planning to move to cloud deployments. Some of these include data backup protection, risk of data leakage, privacy issues, downtime, and limited control over data. This becomes more critical when the PLM instance needs to hold an export control, IP licensed data.

With today’s increasing remote-centric work culture, the ability to enable teams and partners to collaborate via cloud solutions is essential to ensure productivity. The overall objective for most companies implementing PLM in a cloud is to optimize productivity and create a virtual manufacturing paradigm. Read our point of view to learn more about our approach of implementation and the key highlights of deploying Teamcenter on Amazon cloud.

Author


Sangramsinh Ghorpade

Sangramsinh is a Senior PLM solution architect and PLM CoE Lead with industry 4.0 enthusiast working with Capgemini’s Digital Engineering and Manufacturing Services. Expert in business process consulting, PLM implementation in complex business scenarios using rich domain experience and leveraging the latest tools and techniques in the area of Digital Manufacturing, IoT, and Cloud.

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