March 5, 2024

Understanding Product Lifecycle Management


In today’s fast-paced business environment, getting new products to market quickly and efficiently is key to maintaining a competitive edge. However, bringing a product from concept to delivery is a complex process that requires coordination across multiple departments and functions. This is where Product Lifecycle Management (PLM) plays a vital role in streamlining operations. PLM is a strategy used by companies to manage the entire lifecycle of a product from inception, through engineering design and manufacture, to service and disposal. Let’s take a closer look at the basics of PLM.

What is Product Lifecycle Management?
Product Lifecycle Management, or PLM, refers to software applications and business strategies that help organizations manage product information across different stages – from ideation to retirement. Effective PLM allows all critical product data such as designs, costs, suppliers and internal processes to be centralized in a single location for easy access and sharing across teams. Some key features of PLM systems include:

– Computer-aided design (CAD) and computer-aided manufacturing (CAM) tools for engineering functions
– Product data management capabilities for maintaining revision controlled files
– Configurators for configurable product definition and variants
– Integration with enterprise resource planning (ERP) for manufacturing and supply chain execution
– Analytics and reporting features for extracting insights from product data

The goal of PLM is to optimize product processes right from the start by avoiding discrepancies, reducing errors and facilitating collaboration between cross-functional groups involved at different lifecycle stages. When implemented properly, PLM streamlines workflows, improves product quality and traceability while compressing development cycles.

Stages in a Product Lifecycle
A product typically goes through the following distinct stages over its lifespan as managed by a PLM solution:

Development Stage
In this stage, ideas are conceived and the feasibility of new product concepts is evaluated. Engineers and designers leverage CAD tools to sketch initial designs, which are refined through multiple iterative simulations and testing. Cost-benefit analysis is also conducted to ensure project viability. All crucial design data is captured and stored centrally in the PLM system for traceability purposes.

Manufacturing Stage
Once a concept is approved, the manufacturing stage begins where planning activities like sourcing, procurement and production scheduling take place. The finalized design is used to configure factories and tooling requirements through digital manufacturing technologies. Supplier networks are also onboarded onto the PLM platform for effective collaboration.

Production Stage
This involves physically manufacturing the product using the configured plants and equipment. Machining, fabrication, assembly lines etc. are controlled based on the instructions in PLM. Manufacturing execution systems integrate with PLM to capture production data to enhance traceability. Quality procedures ensure compliance to specs.

Service and Maintenance Stage
At this stage, product support needs over the usable lifespan are addressed. Field service teams leverage mobile PLM access to quickly resolve issues. Ongoing customer feedback is gathered and incorporated into future design iterations or upgrades via the PLM system. Spare parts management and repair/maintenance workflows are digitally managed.

Disposal and Retirement Stage
Eventually, products reach end of life either due to dated technology or lack of demand. PLM facilitates formal retirement by archiving all related technical documentation for future reference or compliance needs even after the product is no longer in active production. Environmental standards for disposal are followed.

Benefits of PLM Implementation
The measurable benefits that PLM brings to product-centric organizations include:

– Shortened development cycles: Concurrent engineering is enabled by centralized collaboration across locations and functions.

– Improved product quality: Design defects and non-conformances are minimized through simulations and by capturing lessons from previous products.

– Increased innovation: Resources are freed up to focus on new innovations rather than firefighting errors due to easy access to past product knowledge bases.

– Higher profitability: Costs are reduced through better upstream planning, lower scrap rates and on-time deliveries fulfilling market windows.

– Compliance with standards: Regulatory mandates around traceability, serialization etc. can be met by leveraging complete digital audit trails in PLM.

– Scalability and flexibility: As product portfolios evolve, the PLM system scales to support variable needs through configurable solutions.

– Optimized supply chain performance: Suppliers are integrated early using collaborative PLM for lean synchronization of activities.

In summary, effective PLM deployment helps align people and processes end-to-end to bring safer, better quality and more profitable products to consumers at a faster pace. When combined with complementary digital strategies around IoT, analytics and cloud computing, PLM demonstrates even higher returns on investment.

Conclusion
As Product Lifecycle Management competitive pressures intensify, the ability to smoothly transition from concept to delivery has become a key success factor across industries. By holistically managing critical product information digitally, PLM streamlines complex workflows, facilitates compliance and ultimately improves overall organizational efficiencies to gain an edge. Both multinationals as well as smaller manufacturers are increasingly leveraging this integrated approach for responsive product innovation catering to dynamic customer needs. Implemented strategically using the latest technologies, PLM is set to play an increasingly important business transformation role well into the future.

*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it