Product Lifecycle Management

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Product Lifecycle Management

The concept of product lifecycle management (PLM) in industry is not new. In 1985, when the automaker American Motors Corporation (AMC) was looking for a way to speed up its product development process to compete better against its larger competitors, a new concept was born. After introducing its compact Jeep Cherokee (XJ), the vehicle that launched the modern sport utility vehicle (SUV) market, AMC began development of a new model that later came out as the Jeep Grand Cherokee. The first part in its quest for faster product development was computer-aided design (CAD) software that made its engineers more productive. The second part in this effort was the new communication system that allowed conflicts to be resolved faster, as well as reducing costly engineering changes because all drawings and documents were in a central database.

The product data management was so effective that after AMC was purchased by Chrysler, the system was expanded throughout the enterprise, connecting everyone involved in designing and building products. While an early adopter of PLM technology, Chrysler was able to become the auto industry’s lowest-cost producer, recording development costs that were half of the industry average by the mid-1990s. The concept of managing the entire lifecycle of a product from inception, through engineering design and manufacture, to service and disposal of manufactured products created in the market a whole new concept where people, data, processes and business systems where integrated to provide a product information backbone for the organization and its extended network.

Product lifecycle management can be considered one of the four cornerstones of a manufacturing corporation’s information technology structure. Within PLM there are five primary areas;

  1. Systems engineering (SE)
  2. Product and portfolio m² (PPM)
  3. Product design (CAx)
  4. Manufacturing process management (MPM)
  5. Product Data Management (PDM)

Note: While application software is not required for PLM processes, the business complexity and rate of change requires organizations execute as rapidly as possible. However the integration of the information lifecycle with the product lifecycle has brought new benefits to PLM. For example as of 2009, ICT development (EU-funded PROMISE project 2004–2008) has allowed PLM to extend beyond traditional PLM and integrate sensor data and real time ‘lifecycle event data’ into PLM, as well as allowing this information to be made available to different players in the total lifecycle of an individual product (closing the information loop). This has resulted in the extension of PLM into closed-loop lifecycle management (CL2M).

In the Global University Alliance we have therefore dedicated resources to study and research the following research question: “What is needed for an enterprise to embrace a complete lifecycle approach to product management?”

Enterprise engineering is the discipline of designing and modifying enterprises, and enterprise architecture can be used to clearly describe how an enterprise with a product lifecycle management approach should function, be structured and the tools and skills necessary.

Goal – What is the research focus?

The research endeavours to introduce, capture and continually improve the practice of product lifecycle management in the enterprise architecture reference models for the relevant industries. Product lifecycle management is a comprehensive business approach that promotes complete control of an enterprise’s product, its information and expectations from customers and other stakeholders. The approach incorporates systems engineering, detailed design and product data management to ensure complete coverage of the full lifecycle and integrate all business functions that contribute to product development, realisation and support.

The aim is to encapsulate and elaborate the PLM concept into appropriate reference models, thus establishing best practice. Similar to the way that certain business metrics, processes, competencies and information has a direct relationship to the modules of enterprise resource planning software suites, we aim to also further define and model similar relationships to the various PLM modules.

Research insight – Why are we looking at it?

Competitive product realisation is becoming ever more difficult. Globalisation is introducing more competitors, but also access to more suppliers, while products are becoming more complex and business environments more demanding. It is now more important than ever for enterprises to control their products through the various life cycle stages, from ideation to eventual disposal of the product. Essentially, it calls for the ability of multiple parties (engineering, production, operation, maintenance, etc.) to interact and contribute to the product and to keep accurate information about it.The following is a summary of what drives improved product control:

  • The business environment is becoming increasingly complex, with the ongoing introduction of new regulations and sustainability requirements;
  • Product complexity is rapidly increasing due to the desire for customization and the speed of technological development;
  • Businesses are ever more interdependent and the boundaries between suppliers and customers are constantly overlapping;
  • The globalisation of markets and the improvement of transport and communication networks lead to increased competition and potentially more diverse customers;
  • The identification and capture of growing intellectual property to protect business interests.

Product control is difficult to achieve, because the product changes ownership as it advances through its life cycle phases. For example, during the development phase, engineering is in control of the product, who then hands it over to manufacturing. Furthermore, the product may not yet exist during the idea and development phases. Once the product is sold and delivered to customers, the product is utilised outside the company premises, yet control is still crucial to ensure adequate product support and after-sales service.

Further challenges to managing products across the lifecycle include the following:

  • Products may be part of product lines, which in turn are part of product families and the complete product portfolio. Different products and lines may share common parts.
  • The business may have many products at different phases in the lifecycle.
  • Even if marketing, engineering, manufacturing, SCM and after sales support did their job well, integrated and explicit management of the product across its lifecycle may still cause problems.

The following may occur due to a lack of product control:

  • During product development, the product may be late to market and exceed the targeted cost;
  • During use of the product may cause frustration and a lack of satisfaction for the customer, or much worse, injury and death;
  • For the company, the results may be damage to the company’s image and loss of customers;
  • Loss of revenues because the time to market was too slow;
  • Reduced profit due to costs of recalls and legal liabilities resulting from product use (Stark, 2011).

Research areas

Adopting a PLM approach to business is broad and difficult to comprehend and implement. The research therefore focuses on how to make it easier to understand, embrace and introduce PLM into an enterprise. The following research areas have been identified:

  • What exists: Compare current PLM framework, methods and approaches.
  • What exists: Compare current product lifecycle phases, steps and tools in the PLM frameworks, methods and approaches.
  • What are the necessary product lifecycle phases and steps?
  • What are the basic PLM competencies and capabilities in organizations?
  • Who are the stakeholders of the various product lifecycle phases?
  • Which steps need to be integrated, in terms of flows throughout the product lifecycle?
  • Which models and artifacts are needed to manage a well-structured and valuable product portfolio?
  • Which integrated models and artifacts are needed to manage, control and have visibility over products throughout the lifecycle?
  • Which value and quality gates should exist in the various phases and steps?
  • How would integrated requirement management from business, application to technology be integrated into PLM?
  • How would the disciplines of enterprise modelling, enterprise engineering and enterprise architecture be combined in PLM?
  • How can agile principles be adapted to PLM?
  • How would a PLM taxonomy and ontology look?
  • How would models and artifacts look like to have an integrated PLM taxonomy and ontology?
  • Where are important PLM semantics in terms of relationships of concepts and meta objects?
  • Where could maturity be measure in PLM?
  • Where would maturity models need to have additional context in order to enable cross PLM capabilities?
  • Where would effective feedback loops be from stakeholders, customers, partners, products, field engineers and the market?
  • Why aspects: what are the most common why factors in terms of benefits and value from applying PLM?
  • Why aspects: what are the most common value and performance drivers for PLM?

The following industry reference models and standards is initially targeted to ensure proper treatment of PLM concepts and elements:

  • Aerospace and Defence
  • Automotive
  • Electronic & Electric Equipment
  • Industrial Engineering
  • Automobiles & Parts
  • Airline
  • Railway
  • Shipping
  • Technology Hardware & Equipment

Research contacts

The Product Lifecycle Management (PLM) research contacts are:

Research Coordinator:
Jonnro Erasmus
Enterprise Engineer at the Council for Scientific and Industrial Research (CSIR)

Global University Alliance Coordinator:
Professor Mark von Rosing
Head of Global University Alliance, Denmark

Framework Coordinator:
Henrik von Scheel
LEADing Practice, CEO, Switzerland

The members involved in this work have been a team that includes academics, researchers and analysts:

  • PLM Ontology (meta objects), Professor Wim Laurier
  • PLM Semantics (relations and rules), Professor Simon Polovina
  • PLM Reporting & Information Decision Models, Professor Hans Scheruhn
  • PLM Key Performance Indicators (KPIs), Ulrik Foldager
  • PLM Capabilities, Maria Hove