PLM (Product Lifecycle Management): a key to manage supply chain complexity

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PLM (Product Lifecycle Management): a key to manage supply chain complexity

Imane Bouhaddou, Abdellatif Benabdelhafid

To cite this version:

Imane Bouhaddou, Abdellatif Benabdelhafid. PLM (Product Lifecycle Management): a key to manage

supply chain complexity. CS-DC’15 World e-conference, Sep 2015, Tempe, United States. �hal-

01291112�

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PLM (Product Lifecycle Management): a key to manage supply chain complexity

Imane Bouhaddou

^1,*

and Abdellatif Benabdelhafid

²

1

Ecole Nationale Supérieure d’Arts et Métiers, Morocco b_imane@yahoo.fr

2

Le Havre University, Le Havre, France Abdellatif.benabdelhafid@uni-lehavre.fr

Abstract. The ability to optimize the supply chain is becoming the critical issue for companies to win the competitive advantage.

Furthermore, all members of a given supply chain must work together to respond to the changes of market demands rapidly. PLM enables a supply chain to become much more competitive by an effective collaboration among customers, developers, suppliers and manufacturers at various lifecycle stages of a product.

Our work contributes to the field of integrated engineering, specifically the integrated logistics in the early phases of the product lifecycle using PLM.

The supply chain is a complex system and like any complex system, solutions are found by compromise.

In this paper, we proposed conceptual models to solve formally the compromise between PLM and mathematical models to optimize the supply chain.

With the proposed approach, we have avoided the global optimization of the supply chain (high time solution, approximate solution, complex models, unrealistic hypothesis…) The complexity was treated part by part by local optimization, the solution will be evolved to be more realistic by a continuous optimization.

Keywords: PLM (Product Lifecycle Management), supply chain, product design, supply chain design, optimization mathematical models, integrated logistics.

1 Introduction

Doing business globally involves very complex and increasingly dynamic processes and demands a high level of flexibility and adaptability from the companies involved [1].

Therefore, the complex management of an extended enterprise has increased

needs for information exchange, sharing and archiving.

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A supply chain encompass such entities, as suppliers, manufacturers, assemblers, distributors, logistics centers, customers and in some cases even competitors, which are interconnected among by flows of different resources, including goods, information or finance, through physical and virtual network of their performance

Managing increasing complexity in supply chains is absolutely necessary to companies to compete better in global market. Complexity in supply chains is associated with material and information flows between supply chain partners.

PLM (Product Lifecycle Management) enables a supply chain to become much more competitive by an effective management of the supply chain flows at various lifecycle stages of a product.

2 Supply chain complexity

2.1 Characteristics of supply chain complexity

There are some key characteristics of complexity occurring in a supply chain system which need to be discussed to understand the impact of these characteristics on the occurrence of complexity. These characteristics were detailed in [2]. We summarize them in the following chart:

Table 1. Characteristics of supply chain complexity.

Characteristic Description Number of

components

Number of items (raw, manufactured or end), products, processes, supply chain partners, relationships, interactions, goals, locations,…

Example : A high number level of any components contributes increasingly in a complexity in a supply chain system.

Diversity Related with the homogeneity or heterogeneity of a system Example : A high level of diversity of any components (supplier,

product, mean of transport) along the supply chain leads to system’s heterogenzity heterogeneity and results a high level of complexity.

Interdependency

Variety

Uncertainty

Interdependence between items, products and supply chain partners. Complexity increases in direct proportion to the increase of interdependence.

Variety represents dynamical behaviour of a system.

Example: a product or a process variety in supply chains leads to increase in complexity level over time.

Uncertainty represents all difficulties to be able to make a clear picture of a system due to the lack of information or knowledge.

The more uncertainty in a supply chain system is, the more complexity occurs in this system.

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2.2 Supply chain flows

Complexity in supply chains is associated with material and information flows between supply chain partners. Traditionally, these flows are organized sequentially from supplier to customer. Today, information flows do not follow this linear form. Information flows rather now look like a simultaneous exchange, especially through electronic exchanges between all supply chain partners.

Fig. 1: Material and information flows in supply chain: new pattern [3]

Figure 1 is a schematic diagram of this new pattern. There are internal networks in the firm with simultaneous exchange between all units. Indeed, the emergence of information and communications technology facilitating exchange between all partners, produced a change in the organization of the supply chain flows [4],[5].

In addition, different industrial activities with strong technological character generate and manipulate a lot of technical data that need to be exchanged, managed and stored in a consistent and standardized manner. They have led to the developing of methods and systems to manage the product information throughout its lifecycle. It is in this context that the paradigm of PLM (Product Lifecycle Management) was born [6].

3 Product Lifecycle Management

3. 1 Definition of PLM

To meet the challenges of today's global business environment, organizations with complex products and processes need to manage the entire product lifecycle from concept through end of life, working across functions and supply chain partners. Additionally they must ensure they are able to respond quickly to market opportunities as well as changes in technology and customer requirements [7].

PLM is an integrated approach that, with information technology aid, realizes an

integrated cooperative and collaborative information product management during all the

lifecycle [8]. PLM systems allow simultaneous and collaborative product development

by taking into account all stages of the life cycle [9].

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PLM is an application of manufacturing industry that allows to virtually simulate the complete product life [10]. PLM system should enable the flow of information between different business applications (fig.2). In fact, PLM enables organizations to develop consistent, repeatable processes that extend through the product lifecycle and enable collaboration across system disciplines and the supply chain. The figure 3 represents an analogy with human body. Indeed, informational connections in the human body are connected by the backbone. We consider that PLM plays the role of the backbone.

3. 2 PLM for supply chain optimization

Optimizing the supply chain and especially the simultaneous optimization of product and supply chain design is a difficult problem. Due to the complexity of the induced mathematical models, very few models address the integrated problems. They use a very large number of variables to model the problem in a comprehensive manner and are therefore difficult to solve [13].

Centralized approaches used to treat the problem of integrated design of the product and its supply chain generate complex mathematical models, we adopt an approach combining centralized decisions while integrating the constraints of the different supply chain partners during the product design and decentralized decisions when it comes to locally optimize each supply chain partner.

The decentralized approach reduces the complexity of solving mathematical models and allows the supply chain to respond quickly to the evolution of local conditions of each partner.

Fig. 2: PLM and other applications [11] Fig. 3: Analogy with human body [12]

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PLM will assure the integration of the different supply chain partners. Indeed, the information centralization by the PLM enables to take into consideration the dependence between these partners, improving therefore local optimization results.

The local optimization allows to:

- Decrease the amount of data to be processed in each resolution process.

- Preserve the autonomy of each supply chain partners .

- Respond quickly to the evolution of local conditions of each partner.

With PLM, everyone is contributing to the product design.

The partners of a supply chain are linked by PLM. The PLM structures the design of the supply chain (fig.4).

The mathematical models to optimize the supply chain cost were detailed in [14]. They concerned a problem integrating supplying-production-storage-distribution which aims to minimize the supplying costs, production costs, storage costs and distribution costs.

The models developed are related tostrategic and tactical decisions for supply chain design.

4 Framework PLM/Supply chain optimization

The modelled framework using UML class diagram (figure 5) is based on PLM model [15]

and the methodology for simultaneous design of a new product and its optimized supply chain proposed in our previous paper [16].

It includes the digital mock-up parameters (product in design) and the different variables needed for supply chain optimization.

This framework highlights the interactions between several factors heavily dependent around the product and consequently the many parameters to manage which illustrates the system complexity.

Fig. 4: PLM as an integrator of supply chain partners

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5 Conclusion

The work presented in this paper is related to the field of integrated engineering, specifically the integrated logistics in the early phases of the product lifecycle using PLM. The supply chain is a complex system and like any complex system, solutions are found by compromise.

The objective of the proposed approach is to solve formally the compromise between PLM and mathematical models to optimize the supply chain.

The approach is on the one hand centralized while integrating supply chain constraints and decentralized with a series of local optimizations which avoid the global supply chain optimization.

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