1、Intelligent Products: A survey Gerben G. Meyera, , , Kary Frmlingb, and Jan Holmstrmc, aDepartment of Business Product lifecycle; Software agents; Supply chains; RFIDArticle Outline1. Introduction 1.1. Background 1.2. Paper outline2. What are Intelligent Products 2.1. Definitions of Intelligent Prod
2、ucts 2.1.1. McFarlane et al. 2.1.2. Krkkinen et al. 2.1.3. Vent2.2. Classification of Intelligent Products 2.2.1. Level of intelligence 2.2.2. Location of intelligence 2.2.3. Aggregation level of intelligence 2.2.4. Classification model3. Technologies enabling Intelligent Products 3.1. Automatic Ide
3、ntification and embedded processing 3.2. Distributed information storage and processing 3.2.1. EPC Global 3.2.2. IDURI 3.2.3. WWAI3.3. Agent-based platforms 3.3.1. Portal platforms 3.3.2. Embedded platforms 3.3.3. Surrogate platforms4. Goals of Intelligent Products 4.1. Manufacturing 4.1.1. Producti
4、on planning and control 4.1.2. Customized products 4.1.3. Change-overs4.2. Supply chains 4.2.1. Sending goods 4.2.2. Re-routing of deliveries 4.2.3. Security4.3. Asset management 4.3.1. Efficiency 4.3.2. Service and maintenance4.4. Product lifecycle management 4.4.1. Improved product design, manufac
5、turing and customization 4.4.2. Maintenance 4.4.3. End-of-life management5. Conclusions and future trends References Vitae1. IntroductionThis paper gives an overview of the recently emerged field of Intelligent Products, by analyzing and proposing definitions of what they are and by performing a sur
6、vey of how they have been or can be implemented and used in different application areas. In this context, Intelligent Products and concepts like Smart Products can be used interchangeably. However, Intelligent Products are not a synonym for concepts like Ubiquitous and Pervasive Computing, Ambient I
7、ntelligence, etc. that tend to focus on how human users interact with their environment. The Internet of Things 33 concept could be a better fit, but it tends to be focused rather on connectivity and information exchange than on the “intelligence” of the products. Intelligent Products are not always
8、 invisible and unnoticeable, they are rather reactive actors that are capable of autonomously adapting to changes in their environment. Even though this is still largely a vision for the future, this survey will provide a picture of the current status and how it can evolve towards this vision in dif
9、ferent application areas. Intelligent Products have many facets. In this survey, the concept, technical implementation, and achievable practical goals will be reviewed. Based on that review, a classification of Intelligent Products will be introduced, which distinguishes between three orthogonal (al
10、beit not independent from each other) issues: what is the intelligence of the product, what is the location of intelligence, and whether the product consists of a single entity or if it is an aggregation or composition of several entities. The reason for introducing such a three-dimensional classifi
11、cation is that previously proposed classifications seemed to be under-developed either in the lower or the upper range of “intelligence” and did not necessarily take into account e.g. how the embedded processing capabilities affect the implementation of such Intelligent Products. Previous classifica
12、tions also tend to focus only on limited parts of a products lifecycle, e.g. manufacturing or maintenance only, rather than taking into account the entire lifecycle. Analyzing different approaches to Intelligent Products using the proposed three-dimensional classification makes it easier to identify
13、 what their limitations are, and which are the main aspects that need further development.Furthermore, the technical foundations of Intelligent Products will be discussed in detail in this survey. These foundations can mainly be found in the areas of automatic identification and embedded processing,
14、 distributed information storage and processing, and agent-based systems. In order to keep the survey reasonably limited, some other relevant domains such as technologies for fault detection and remote maintenance are largely omitted from this survey. For these domains, there already exists dedicate
15、d journals and other dissemination channels. Also, challenges related to privacy, security, trust, etc. are not discussed in detail here, but such aspects in the context of Intelligent Products are discussed in detail in e.g. 35, 50, 51 and 71. Some other challenges for implementing Intelligent Prod
16、ucts, such as the cost and the availability of skilled personnel are pointed out in e.g. 23 and 45.Regarding how, when and why to implement Intelligent Products, the achievable goals for the Intelligent Product concept will be presented as a starting point for developing practical business cases in
17、individual companies. It is important to note that solutions developed for one purpose can, if appropriately designed, be employed for other purposes as well. Means-ends propositions 68 for Intelligent Products in specific contexts will be discussed, such as manufacturing, supply chain, and asset ma
18、nagement, as well as across contexts, i.e. for product life cycle management.1.1. BackgroundIn the early days, factories were often powered by one central steam engine. As mentioned in 10, the electric engine was meant to replace the steam engine. Just as there was one steam engine that would power
19、an entire factory, the electric motor was also initially a single device installed at a central location in the factory, with belts running to the remote areas of the factory. The electric motor improved to the point where a single motor with belts could be replaced by motors built into each device.
20、 Now you could place the instruments wherever it made sense to put them, and the motor became an invisible part of the instrument.According to Norman 60, computers and computer networks should be thought of as infrastructure. It should be quiet, invisible and unobtrusive, instead of being too visibl
21、e and too demanding. He therefore envisages a change occurring from one centrally located infrastructure (the personal computer), to a set of rather small, widely distributed devices. These devices will not even be thought of as computers or telecommunication devices. Instead, these devices will be
22、seen as a natural part of our daily activities and the tools that we use 10. He argues that the proper way to achieve this is through the user-centered, humane technology of appliances, where the technology of the computer disappears behind the scenes into task-specific devices that maintain all the
23、 power without the difficulties 60. Similar views about computing had earlier been proposed mainly under the name ubiquitous computing (see e.g. 80 and 81), that is also sometimes called pervasive computing or ambient intelligence depending on the context.Gershenfeld shares this vision, as he calls
24、invisibility the missing goal in computing 34. According to him, we can bring technology so close to people that it can finally disappear. Furthermore, he emphasizes that the barrier between digital information and our physical world should be removed. The real challenge in this is to figure out how
25、 to create systems with many components that can work together and adapt to changes in the physical world. This vision has sometimes been called the Internet of Things, which is also adopted e.g. in 13, 33 and 36. However, in many contexts such as Supply Chain Management, the Internet of Things conc
26、ept tends to be focused on product identification technologies, information storage and information exchange rather than on the “intelligence” of the products.It seems like Intelligent Products were first discussed in an after sales and service context in 1988 by Ives and Vitale 37. The first exampl
27、es of Intelligent Products in the after sale context were computers running programs that tracked the configuration and performance, and could request for service and maintenance. The benefits in efficiency of service and reliability of operation could be substantial and was the basis for successful
28、 start-ups and new lines of business for established companies.Only later did the idea of integrating intelligence and control into the product spread to manufacturing 55 and supply chain control 47. In these application domains, new auto identification (Auto-ID) technologies, such as radio frequenc
29、y identification (RFID) have made the tracking and tracing of products throughout the entire supply chain possible. When product individuals in a logistic/production setting are not only given a traceable individuality, but also the associated content (e.g. delivery terms, contract terms, exceptions
30、, etc.), and also decision power is delegated to them, we enter the realm of Intelligent Products. Such Intelligent Products will have the means to communicate between themselves and also with logistic service providers. Intelligent Products link the Auto-ID technology to the agent paradigm and Arti
31、ficial Intelligence. Agent technology has already been considered as an important approach for developing industrial distributed systems (e.g. intelligent manufacturing systems) 39, 40 and 66.Intelligent Products can also play an essential role in product lifecycle management by their capability of
32、collecting usage information and reacting on it proactively, e.g. estimating needs for maintenance or repair 62. By using sensor technologies like thermal, acoustic, visual, infrared, magnetic seismic or radar sensors the conditions of products can be continuously monitored. The access to informatio
33、n on how products have been used could significantly improve the way that products are recycled when they arrive to their end-of-life. Sensor technologies can also contribute to improvements in manufacturing nodes and to the logistics of the entire supply chain, by giving real-time status informatio
34、n (e.g. identification, location and other conditions) of the products.What is common to such tracking and tracing in the supply chain and to product lifecycle management is that information needs to be represented at the item level and communicated between different organizations. From an informati
35、on system perspective, a shipment is indeed just a “product” with a relatively short lifecycle, where the actual products that were included in the shipment may have a much longer lifecycle. However, currently used information systems typically focus on managing batches and accounts using centralize
36、d databases, hence representing item-level information and communicating it between organizations can be a challenge for them, in case of mass-customization of products. Therefore, there is increasing interest in the development of Auto-ID technologies and Intelligent Products which is being reflect
37、ed in on-going work, current project proposals and future research areas.1.2. Paper outlineAfter this introduction, Section 2 will analyze different proposals for defining Intelligent Products. Furthermore, a classification method for such products that can be used as a tool for classifying the diff
38、erent implementation approaches will be presented. Section 3 gives an overview of the enabling technologies of Intelligent Products. Section 4 will analyze how Intelligent Products can be implemented and used in different application domains, followed by conclusions and future trends in Section 5.2.
39、 What are Intelligent ProductsThis section will start with presenting existing definitions of Intelligent Products found in the literature. All these definitions focus on certain aspects of Intelligent Products and on certain application areas or parts of the product lifecycle. Afterwards, based on
40、the existing definitions, a classification of Intelligent Products will be proposed, which tries to cover all aspects of Intelligent Products while taking into account the whole product lifecycle.2.1. Definitions of Intelligent ProductsFrom the existing definitions of Intelligent Products, the compl
41、ementary notions of McFarlane et al., Krkkinen et al. and Vent will be discussed next.2.1.1. McFarlane et al.McFarlane et al. define an Intelligent Product as a physical and information-based representation of a product 55. Fig. 1 shows an example of such a product. In this figure, the jar of spaghe
42、tti sauce is the physical product, the information-based representation of the product is stored in the database, and the intelligence is provided by the decision making agent. The connection between the physical product and the information-based representation is made using a tag and a reader, as w
43、ill be further discussed in Section 3.1. According to McFarlane et al., an Intelligent Product has the following properties: 1. Possesses a unique identification. 2. Is capable of communicating effectively with its environment.3. Can retain or store data about itself.4. Deploys a language to display
44、 its features, production requirements, etc.5. Is capable of participating in or making decisions relevant to its own destiny.Full-size image (15K)Fig. 1. Intelligent jar of spaghetti sauce (from 82).Based on this definition, Wong et al. 82 have defined a two-level classification of intelligence. Wh
45、en the Intelligent Product only covers points 13, it is information oriented, and is called a product with level 1 product intelligence. A product with level 2 product intelligence covers all points, and is called decision oriented. Even though this Intelligent Product classification is quite generi
46、c concerning the level of intelligence of an Intelligent Product, it is based on a separation between the actual product and its information-based counterpart (as seen in Fig. 1). Therefore, it is mainly intended for describing the use of RFID technology in for example manufacturing and supply chain
47、 purposes, without covering for instance products with embedded processing and communication capabilities.2.1.2. Krkkinen et al.The fundamental idea behind an Intelligent Product according to Krkkinen et al. 47 is the inside-out control of the supply chain deliverables and of products during their l
48、ifecycle. In other words, the product individuals in the supply chain themselves are in control of where they are going, and how they should be handled. To move to inside-out control of products, the products should possess the following properties: 1. Globally unique identification code. 2. Links t
49、o information sources about the product across organizational borders, either included in the identification code itself or accessible by some look-up mechanism.3. Can communicate what needs to be done with them to information systems and users when needed (even pro-actively).In this definition, the classification goes from no intelligence (unique identification only) towards decision-oriented products when covering the last property, in a similar way to the classification by McFarlane et al. Despite a slightly bigger con
