Chapter 1
Introduction
Abstract
In the past two decades, advanced manufacturing systems (AMSs) were undergoing a lot of changes, and revealed the developing trends and requirements of informatization, globalization, and servitization. However, there still exist some bottlenecks of digitization, interconnection, collaboration, intelligentization, and so on. For example, how to achieve the whole production process of IntelliSense, access, and processing, how to realize the intelligent management of manufacturing resources, etc. Driven by these trends and requirements, lots of new information technologies are applied into AMSs to address these bottlenecks, especially the technology of Internet of things (IoT). In this chapter, the concept of IoT is introduced, and the existing typical manufacturing paradigms of AMSs and their limitations are summarized at first. According to the investigation on the applications of IoT in AMSs, the conception of IoT-based manufacturing system (IoT-MS) is proposed, and the corresponding key features of IoT-MS are pointed out. At last, the systematical organization of this book is described.
Keywords
Internet of things (IoT)
manufacturing system (MS)
limitations
IntelliSense
access
1.1. The concept of IoT
As one of the most important new information technologies, Internet of things (IoT) has attracted great attention from governments, industries, and academia. For instance, the US National Intelligence Council has considered it as one of the six “Disruptive Civil Technologies” with potential impacts on US national power [1]. In 2009, European Union issued a report named “Internet of Things—An action plan for Europe.” This report proposed that it is essential to take measures to ensure that Europe plays a leading role in the construction of new Internet [2], namely IoT. Besides, IoT was also officially listed as one of the five emerging strategic industries by Chinese government in 2010.
Originated from the radio frequency identification (RFID) system, it was first proposed by professor Ashton of MIT Auto-ID Labs in 1999. In 2001, Christopher in University of California proposed the concept of Smart Dust [3]. In 2003, Metro opened the first “future store” [4]. In 2005, Wal-Mart announced that the 100 largest retail stores would start to use RFID tag uniformly. In the Tunis World Summit on Information Society in 2005, the International Telecommunications Union (ITU) extended concept of IoT largely in the report of “ITU Internet Reports 2005 Executive Summary: The Internet of Things.” As the explanation by ITU, it means the intelligent connectivity for anything at anytime and anywhere [5].
After 10 years of development, the new generation of information technologies has been highly integrated with IoT. In this context, the meaning of IoT is also constantly changing. Therefore, so far there is no clear and uniform definition about IoT, especially its various application backgrounds. It syntactically is composed of two terms which are “Internet” and “Things.” Therefore, IoT can be understood from two perspectives, which are “Internet oriented” and “Things oriented” [6]. On one hand, from the perspective of “Things oriented,” it refers to be based on standard communication protocols, and to form a worldwide network [7]. In other words, it is composed of a large number of things, which have identities and virtual personalities. In addition, these things are sustainable, enhanceable, and uniquely identified [8]. On the other hand, from the perspective of “Internet oriented,” it can be considered as the expansion of Internet applications. As a light protocol, IP stack that already connects a huge amount of communicating device, have all the qualities to make IoT a reality [6].
In conclusion, based on “Internet,” IoT extends and expands terminal of Internet to any objects and items. As a result, IoT constructs a network that covers everything in the world as well as the things in this network are able to exchange information and communicate with each other. Substantially, in order to achieve intelligent identification, positioning, tracking, monitoring, and management, everything in IoT is connected with Internet according to the arranged protocol by RFID, infrared sensor, global positioning system (GPS), laser scanner, and other information sensing equipment. Pervasive presence in IoT of a variety of things or objects, such as RFID tags, sensors, actuators, mobile phones, and so on are able to interact and cooperate with each other through unique addressing schemes to reach common goals [9] without human intervention. In addition, under the influence of related researches and developments, IoT has developed connection among different things to the combination and integration of information space and physical world.
The original architecture of IoT can be abstracted as perception layer, network layer, and application layer. However, the existing researches increasingly focus on ubiquitous service application of IoT. Therefore, according to the collection, transmission, processing, and application process of multisource information, the extended IoT architecture can be broadly summarized as perception layer, transmission layer, the cloud platform layer, and application layer, as shown in Fig. 1.1. The perception/sensing layer mainly achieves the ubiquitous object recognition and operation control. The transmission layer mainly realizes data acquisition and transmission. The cloud platform layer mainly conducts the corresponding information integration and data processing to support the ubiquitous service management and application. The application layer provides user interfaces for the applications of ubiquitous services of IoT combining related industries’ demand.
Figure 1.1 The general architecture of IoT.
At present, IoT has got good applications in a number of fields and industries. These applications can be grouped into the four domains [6]: (1) transportation and logistics domain, including logistics, assisted driving, mobile ticketing, monitoring environmental parameters, augmented maps, and so on, (2) healthcare domain, including tracking, identification and authentication, data collection, sensing, and others, (3) smart environment (home, office, and plant) domain, such as comfortable homes and offices, smart building, smart cities, industrial plants, smart museum, gym, and so on, and (4) personal and social domain, including social networking, historical queries, losses, thefts, and so forth.
1.2. Existing manufacturing paradigms and their limitations
1.2.1. Agile Manufacturing
In 1991, a group of more than 150 industry executives participated in a study to meet the coming global challenges and revive the US manufacturing treasures. Their efforts culminated in a two-volume report titled “21st Century Manufacturing Enterprise Strategy” [10]. As a result, the Agility Manufacturing Enterprise Forum (AMEF) affiliated with the Iacocca Institute at Lehigh University, was formed and the concept of agile manufacturing (AM) was introduced [11–14].
AM is an approach to manufacturing which is focused on meeting the needs of customers while maintaining high quality and controlling the overall costs involved in the production of a particular product. This approach is geared toward companies working in a highly competitive environment, where small variations in performance and product delivery can make a huge difference in the long term to a company’s survival and reputation among consumers. The goal of AM is to keep a company stand out in the competition so that consumers will give priority to the company. Financial stability and strong customer support make it possible for the company to spend more on innovations. Companies which utilize an AM approach tend to have very strong networks with suppliers and related companies, along with numerous cooperative teams which work within the company to deliver products effectively. They can reconfigure facilities quickly, negotiate new agreements with suppliers and other partners in response to changing market forces, and take other steps to meet customer demands. This means that the company can increase the value of production with a high consumer demand, as well as redesign products to respond to issues which have emerged on the open market. The principles of AM are shown in Fig. 1.2.
The appearance of AM has prompted manufacturing enterprises to enter into the organizational mode of enterprise integration. In an environment with growing customized demands, computer network technology (CNT), supply chain management (SCM), and other related technologies have been developed rapidly. They enhance the agility, globalization of manufacturing operations. This period witnessed the rapid development of mass customization with the aim to achieve the economy of scope. However, analyzing the concept of AM, several issues need to be investigated, including how to acquire the need of customers, how to achieve on-demand use of various manufacturing resources, and how to establish the strong network with suppliers and related companies as mentioned previously. The technology of IoT and the strategies of on-demand use scheduling are the bottlenecks to achieve AM according to the issues.
1.2.2. Networked Manufacturing
Networked manufacturing (NM) means that manufacturing enterprises carry out product design, manufacturing, sales, procurement, management, and a series of activities based on network technology especially the Internet. It provides the environment and implementation methods for enterprises to develop remote collaborative design and manufacturing, online marketing, SCM, through the information integration, business process integration, and resource sharing among enterprises of different locations. NM can not only achieve the collaborations of product commerce, product design, product manufacturing, and supply chain, but also shorten the product development cycle, reduce research costs and improve the competitiveness of the whole industry chain [16–19], as shown in Fig. 1.3.
Technologies involved in NM can be divided into four parts, including overall technology, basic technology, integration technology, and application technology [21]. (1) Overall technology mainly refers to the technologies about the structure, management and application of NM system from the systematic point of view, for example, NM mode, the architecture of NM system, construction and organization methods, operation and management strategies, product life cycle management and collaborative product commerce technology. (2) Basic technology is the common and basic technology that is used not only in NM systems, but also in many other information systems, for example, basic theory and methods of NM, protocols and standardization technology of NM system, product modeling and enterprise modeling technology, workflow technology, multiagent system technology, virtual enterprises and dynamic alliance technology, and knowledge management and integration technology. (3) Integration technology contains the system integration and enabling technologies used in design, development, and application implementation of NM systems, for example, design/manufacturing resource and knowledge libraries technology, enterprise application integration technology, integration platform technology, ASP service platform technology, ecommerce and EDI technology, Web service technology, and so on. (4) Application technology refers to the technology involved in the application implementation of NM systems, for example, the approaches of NM application implementation, basic data library building and management technology, resource encapsulation and interface technology, cooperation technology in virtual enterprise, and network security technology.
However, in the practical application of NM, intelligent perception and connection of underlying physical manufacturing resources are the two key issues which hinder the development of NM. Although NM is developed on the basis of AM, the issue of how to achieve on-demand use is still unresolved. What’s more, the low-degree servitization of manufacturing resource also is a bottleneck of NM.
1.2.3. Reconfigurable Manufacturing Systems
In 1995, researches of University of Michigan submitted a proposal to NSF for establishing a research center on reconfigurable manufacturing systems (RMSs) [22]. RMS is a new paradigm that attempts to link market demands and manufacturing systems by increasing flexibility of the system configurations. RMS is designed at the outset for rapid changes in structure, as well as in hardware and software components, in order to adjust production capacity and functionality quickly within a part family in response to sudden changes in market or in regulatory requirements [23].
As one of the components of RMSs, the reconfigurable machine tool (RMT) was invented in 1999 in the Engineering Research Center for Reconfigurable Manufacturing Systems (ERC/RMS) of University of Michigan [24]. The components of RMS are CNC machines, RMT, reconfigurable inspection machines and material transport systems (such as gantries and conveyors), which form the system. Different arrangements and configurations of these machines will have an impact on the system productivity. A collection of mathematical tools, which are defined as the RMS science base, may be utilized to maximize system productivity with the smallest possible number of machines.
Ideal RMSs possess six core characteristics, that is, modularity, integrability, customized flexibility, scalability, convertibility, and diagnosability [23–28]. These characteristics, which were introduced by Professor Yoram Koren in 1995, apply to the design of whole manufacturing systems, as well as to some of its components, including reconfigurable machines, controllers, and system control software, described as follows.
1.2.3.1. Modularity
In an RMS, all major components are modular (e.g., structural elements, axes, controls, software, and tooling). The benefits of modularity include economies of scale, increased feasibility of product/component change, increased product variety, reduced lead time, easier product diagnosis, maintenance, repair, and disposal [25,28].
1.2.3.2. Integrability
It is the ability to integrate modules rapidly and precisely by a set of mechanical, informational, and control interfaces enabling integration and communication. At the machine level, axes of motions and spindles can be integrated to form machines. Integration rules allow machine designers to relate clusters of part features and their corresponding machining operations to machine modules, which enables product–process integration. At the system level, the machines are the modules that are integrated via material transport systems (such as conveyors and gantries) to form a reconfigurable system. To aid in designing reconfigurable systems, system configuration rules are utilized. In addition, machine controllers can be designed for integration into a factory control system.
1.2.3.3. Customization
This characteristic drastically distinguishes RMS from flexible manufacturing systems (FMS), and has two aspects: customized flexibility and customized control. Customized flexibility means that machines are built around parts of the family that are being manufactured and provide only the flexibility needed for those specific parts, thereby reducing cost. Customized control is achieved by integrating control modules with the aid of open-architecture technology, providing the exact control functions needed [28].
1.2.3.4. Convertibility
It is the ability to easily transform the functionality of existing systems, machines, and controls to suit new production requirements [28]. Shorter conversion time between different production batches is a major requirement. To achieve this, the RMS must utilize not only conventional methods such as offline setting, but it should also contain advanced mechanisms that allow for easy conversion between parts, as well as sensing and control methods that enable quick calibration of the machines after conversion.
1.2.3.5. Scalability
It is the ability to easily change production capacity by rearranging an existing manufacturing system and/or changing the production capacity of reconfigurable stations [28]. Scalability is the counterpart characteristic of convertibility. Scalability may require at the machine level adding spindles to a machine to increase its productivity, and at the system level changing part routing or adding machines to expand the overall system capacity (i.e., maximum possible volume) as the market for the product grows.
1.2.3.6. Diagnosability
It is the ability to automatically read the current state of a system for detecting and diagnosing the root-cause of output product defects, and subsequently correct operational defects quickly [28]. Diagnosability has two aspects, including detecting machine failure and detecting unacceptable part quality. The second aspect is critical in RMS. As production systems are more reconfigurable, and their layouts are modified more frequently, it becomes essential to rapidly tune (or ramp-up) the newly reconfigured system so that it produces quality parts. Consequently, reconfigurable systems must also be designed with product quality measurement systems as an integral part.
In order to achieve RMS, several issues need to be investigated first, including how to link market demands and RMS, how to increase flexibility of the system configuration, and how to adjust quickly production capacity and functionality in response to sudden changes in market. However, related technologies to solve the aforementioned issues are relatively immature, for example, IoT technology, service-oriented technology (SOT), service management technology, on-demand use scheduling technology.
1.2.4. Product-Service System/Industrial Product-Service Systems
As industrialized countries are subject to a structural change toward a service society in which product services would meet users’ demands, promote product innovation, be ecologically friendly, improve competitive strength, and be driven by new IT, product-service system (PSS)/industrial product-service system (IPS2) is developing rapidly as a new manufacturing system mode [29]. Services can be seen as add-ons to the actual product instead of the independent development in different departments. It links tangible products and intangible services, in order to change traditional manufacturing/consumption mode and solve environmental issues [30]. PSS is often defined as customers’ life cycle–oriented combinations of products and services, realized in an extended value creation network, comprising a manufacturer as well as suppliers and service partners [31]. Similarly, IPS2 is sometimes characterized by the integrated and mutually determined planning, development, provision, and use of product and service shares including its immanent software components in business-to-business applications and represents a knowledge-intensive sociotechnical system [32]. The distinction between them is the integrated development of the mutually determined product and service shares is essential for IPS2. They all represent an integrated physical product and nonphysical service offering that delivers value in use. Essentially, PSS and IPS2 are usually mentioned as a similar conception.
The key research technologies of PSS/IPS2 could be classified into five categories as follows [33]. (1) Product service−oriented product design technology. Although there are great differences between different users for product service, some common demands among users exist. Therefore, modularization technology can satisfy the flexibility and reduce costs. At the same time, service-oriented reliability design, green design, and intelligence design should be taken into account. (2) Product service–oriented user demand mining technology. User demand could be mined through product service and social media. Furthermore, users can be involved in the enterprise innovation for the better understanding by enterprise. (3) Service-oriented product maintenance technology, such as remote diagnostics and maintenance, PMA, maintenance visualization, IETM, and knowledge service. (4) Product service–oriented information acquisition techniques, such as RFID and rapid measuring technology. (5) Product service–oriented user experience, such as an artificial emotion service robot and experiential marketing.
As the PSS/IPS2 develops, characters of product service differ from traditional ones. A holistic management approach as well as powerful methods and tools are compulsory for an IPS2 life cycle management. Existing product life cycle management requires several extensions for the better development, such as management of integrated product and services, dynamic customer-specific objects, interconnection of providers/customers, value-added processes, quality, and some other adaptions for different domains.
In a word, PSS/IPS2 leads the paradigm shift from traditional standardization and mass production into flexible and mass consumption which is driven by the additional value rather than price. However, there are some key issues that need to be investigated first, including how to acquire information about product and user efficiently and how to obtain users’ demand accurately.
1.2.5. Manufacturing Grid
Manufacturing grid (MGrid) was first put forward in 2003 when information technology was experiencing the third wave of grid technology after the proliferation of the Internet and web technology [34]. Grid technology whose key concepts are resource sharing and coordinated problem solving in a virtual organization [35] can solve the very two bottlenecks that hinder the development of the current modes of manufacturing. In a grid system, users can obtain the services to fulfill their specific manufacturing requirements because of the connectivity and the operability among distributed and heterogeneous resources. Therefore, MGrid was put forward under this scenario while VM organizations based on grid technologies have gradually evolved to be a new manufacturing paradigm under a network-centric environment. In addition, some key technologies for implementing MGrid are adopted from computing grid.
Based on several related influential concepts of MGrid, the definition can be summarized as MGrid is to utilize grid, information, computer and advanced management, and advanced manufacturing technologies, etc. to overcome the barrier resulting from spatial distances in collaboration among different corporations to allow dispersed manufacturing resources (including design, manufacturing, human, and application system resources) to be fully connected, and it is a manufacturing service pool supporting manufacturing resource sharing, integration, and interoperability among different enterprises [36]. MGrid is indeed a realization of sharing various resources. Users can use all the resources distributed in heterogeneous systems and locations in MGrid as conveniently as they use local resources.
The key research contents and technologies of MGrid can be divided into the following four categories [37]. (1) The category of general technologies includes all the fundamental and necessary technologies such as concept, architecture, model, and management in manufacturing mode. (2) The category of supporting technologies includes the technologies supporting MGrid operation and system integration such as communication, security, and grid technologies. (3) The category of key enabling technologies include resource- and service-related technologies, management technologies, data and knowledge mining, payment, and evaluation. (4) The category of application technologies includes the interaction, visualization, cooperation, and portal-related technologies.
In addition, the related MGrid theories can be classified into the following categories. (1) Architecture of MGrid: different forms of MGrid architecture which decide the functions and basic modules have been proposed. (2) Resource management system: Resource management system is the central component of an MGrid system. (3) Modeling and encapsulation of MGrid resource: it is to enable MGrid resource information to be published and registered in an MGrid system. (4) Resource service discovery and scheduling: it emphasizes on search mechanisms or frameworks at the abstract level, resource match and search method from the descriptive information of resource service, service scheduling methods considering the factors of dynamic, intelligence degree and so on. (5) QoS management: it has been investigated from different perspectives of QoS whole-life cycle management, MGrid architecture view and QoS attribute parameter. (6) Service composition: MGrid system generates a new composite resource service and selects the optimal resource service composite path from all the possible paths to execute the task. (7) Workflow management: it has been widely investigated to enable users to compose and execute complex grid applications with distributed heterogeneous and unreliable computing resources. (8) Job management: it is primarily responsible for the whole-life cycle management of MGrid jobs that are anything that needs resource services. (9) Reliability management: reliability is a significant and complex issue in an MGrid system. (10) Security and trust management: the security problem is the key bottleneck that hinders the development and application of MGrid. (11) Others such as MGrid portal design, semantic support, and performance evaluation are also key theories of MGrid.
Although MGrid experiences a period of rapid development and research, some key issues such as embedded connect problems of physical manufacturing facilities, uniform protocols/standards and reliability problems still hinder the progress of MGrid.
1.2.6. Cloud Manufacturing
Cloud manufacturing (CMfg) is a computing- and service-oriented manufacturing model combining the emerged advanced technologies [e.g., cloud computing (CC), IoT, virtualization, and SOTs, advanced computing technologies (ACTs)] [38] with existing advanced manufacturing models (e.g., AM, NM, PSS/IPS2, MGrid) and enterprise information technologies. Users (e.g., provider, operator, and consumer) can easily have access to the manufacturing cloud services virtualized and encapsulated from the distributed manufacturing resources and manufacturing capabilities [39].
The first definition of CMfg was proposed in 2010, and then this new concept attracted much attention from both academic and industry communities. CMfg is a service-oriented, highly efficient and low consumptive, knowledge-based and intelligent networked AM model and technology, allowing manufacturing resources and capabilities to be virtualized and transformed into on-demand services available to users through a product life cycle [40]. Unfortunately, there still lacks a commonly accepted definition for CMfg, but some common terms, such as manufacturing resource, capability and platform, virtualization and cloud service are shared in different definitions. It is a promising manufacturing paradigm that is built on CC, IoT, cyber-physical systems (CPS), NM, service-oriented manufacturing, and virtual manufacturing.
Although existing research articles in this area present some system architectures that are have slightly different system structures, almost all of them share some similar elements, such as resource virtualization and cloud service composition. A popular hierarchical structure of CMfg system is divided into ten layers, as shown in Fig. 1.4. Resource layer, perception layer, resource virtualization layer, cloud service layer, application layer, portal layer, enterprise cooperation application layer, knowledge layer, cloud security layer and wider Internet layer (e.g., Internet, intranet, IoT). The details are shown in the Fig. 1.4. Core technologies (e.g., CC, IoT technologies, virtualization, SOTs, ACTs, existing manufacturing informationization technologies) will support the construction of the CMfg hierarchical structure.
Compared with existing manufacturing models, CMfg has several typical characteristics: service- and requirement-oriented, dynamic with uncertainty, knowledge-based initiative, physically distributed and logically centralized, Wikipedia style and group innovation-based manufacturing, lower threshold, and outsourcing. Based on the aforementioned typical characteristics, CMfg can offer several key advantages, such as (1) reducing resource idle capacity and increasing utilization, (2) reducing the up-front investments and lowering the cost of entry for SMEs trying to benefit from high-value manufacturing resources (e.g., high-end equipment, expensive application systems) and specific manufacturing abilities that were hitherto available only to the larger corporations, (3) reducing infrastructure and administrative cost, energy saving, upgrades and maintenance cost, (4) easier for manufacturing enterprises (both smaller and larger) to scale their production and business according to client demand, (5) generating new types and classes of manufacturing/business model or process, (6) optimizing industrial distribution and speeding up the transformation from a distributed and high-energy consumption manufacturing model to a centralized, and environment friendly manufacturing model, and from production-oriented manufacturing to service-oriented manufacturing.
For implementing CMfg, intelligent perception and connection technologies for various physical manufacturing resources and abilities are the fundamental technologies. However, because of the diversity of physical manufacturing resources and capabilities, how to interconnect these different resources is still one of the most important challenges.
1.2.7. Limitations
After 20 years of development, these AMSs have played a very important role in developing modern manufacturing and industry, and in realizing goals of TQCSEFK (i.e., fastest Time-to-market, highest Quality, lowest Cost, best Service, cleanest Environment, greatest Flexibility, and high Knowledge). More and more AMSs devote to adapt to the trends and requirements of informatization, globalization, and servitization of manufacturing, and a lot of key technologies have been studied, including manufacturing resource and service modeling and encapsulation, resource and service optimal-allocation and scheduling, service workflow management, SCM, etc.
However, the socializations of the resources sharing, value creation, users’ participation, supply–demand matching, on-demand use, and personalization in manufacturing run much clearer and faster as shown in Fig. 1.5. Due to the lack of common specifications and standards, the application of AMSs is hindered without realizing intelligent perception and connection of underlying physical manufacturing resources to Internet. As well, the low-degree servitization of MRs&Cs based on knowledge, limits the number, ability, and usage mode of services provided to users. In addition, due to the lack of effective operational mechanisms of resources and services and reliable safety solutions, it makes the application and development of the AMSs difficulty. Finally, the on-demand management of MRs&Cs is also the bottleneck to achieve the collaboration and intelligence of AMSs.
At the same time, SOTs, ACTs, virtualization technology, embedded technology, CPS, CC, IoT, have been quickly developed and widely applied. These new technologies have provided new methods for addressing the bottlenecks faced by the existing AMSs. For example, SOTs such as service-oriented architecture, web service, ontology, and semantic web, can provide enabling technologies for the construction of a virtual manufacturing and service environment. ACTs such as high-performance computing technologies, grid computing, parallel computing, can provide enabling technologies for solving complex and large-scale problems. Virtualization technology can hide the physical characteristics of the manufacturing resource and capability in an AMS from users. IoT technology can realize the effective connection, communication, and control from physical world to information world. Especially, as providing the new method for intelligent perception and connection of anything, and the on-demand use and efficient sharing of resources respectively, IoT and CC have been widely studied and applied in many fields. As a result, in order to realize the full sharing, free circulation, on-demand use, and optimal allocation of various MRs&Cs, it needs to investigate the applications of the theories and technologies of IoT in manufacturing at first.
1.3. Applications of IoT in manufacturing system
So far, there still is no clear and uniform definition and architecture about IoT, it has been used in various application backgrounds. For instance, the applications of smart homes or smart buildings, smart cities, smart business, smart inventory and product management, healthcare, environmental monitoring, social security and surveillance, and so on [43]. Especially, it has been fundamentally changing the practical production and supply chain process and management with the aim of intelligent manufacturing.
Specifically, after introducing the generalized IoT into manufacturing industry, it can be devoted to address the “4Cs” (Connection, Communication, Computing, and Control) of MRs&Cs for the following different applications in manufacturing [42], as shown in Fig. 1.6. (1) Applications in the workshop. It can achieve the complete connection between terminal devices (i.e., various MRs&Cs) and the enterprise information management system for the automatic control of the IoT-enabled manufacturing execution in workshops. Therefore, three functions should be addressed: the access, identification, and control of the physical manufacturing execution process from materials and semifinished products to the final products. The data identified and acquired from the IoT-enabled manufacturing layer are the production- and product-related input of the enterprise information system. Moreover, the automatic control of manufacturing execution activities is the result under the output of the system to the PLC and other controllers. It is the general applications of IoT in workshops. (2) Applications in the enterprise. It promotes the integration of the production-related information, the product-related information, and other business management information, as well as the integration of the IoT-based workshop and other enterprise information subsystems. Enterprises can generate their own manufacturing services for the participation into the external supply chain, in addition to the management of the internal supply chain. It results in the origin of the local Internet of services (IoS). (3) Applications among enterprises. It addresses the information integration, storage, retrieval, analysis, use, data security, and other issues during these ubiquitous service management and application process among massive different enterprises. Consequently, CC and cloud platform technologies provide the new ideas and technical supports for the ubiquitous networking service management and application of IoT.
Besides, IoT has another important application in IoT-based energy management in product life cycle.
1. Simulation and testing of product
Simulation and testing of product is a significant phase of product life cycle. Every small mistake during this process can lead to the abnormal product operation. One of the main challenges of this phase is to collect enormous amount of test data and analyze the data effectively. Nowadays, with the help of IoT, test data generated by IoT equipment is available. Then product designer and technical analysts can make energy-efficient decisions from the data connected with different kinds of influence factors.
2. Public facilities real-time monitoring
Sensing terminals collect energy consumption information of water, electricity, gas, and heating. By comparing energy consumption for the same process in different environments and analyzing through the combination of quality of product, processing time, and energy-related data, the energy consumption condition of public facilities can be improved accordingly.
3. Efficient working way of manufacturing equipment
The key to decrease the energy consumption in the manufacturing phase is improving the principles and configurations of equipment. With the help of IoT, equipment status and related parameters can be accurately collected. The power generation processes can be evaluated as well. Knowing equipment energy consumption pattern in real-time enables reducing energy consumption at peak time and reducing idle time by switching a machine off. Defining energy consumption for a machine in different configurations and choosing a more efficient machine configuration also decrease the energy consumption. In addition, as the manufacturing process is monitored in real time, the unqualified semifinished products can be discovered at once to avoid more energy waste.
4. Efficient transport planning
With the IoT, transport networks and product location tracking can be realized easily so as to improve energy efficiency in transportation phase. For example, “Energy Cards” have been used to determine and reduce energy demand in the logistics area. And some companies share transportation with other companies which share the same destination or transportation route to deliver products in order to achieve higher energy efficiency.
5. Energy conservation use guide
In utility phase, energy consumption can be easily generated by inappropriate behaviors of customers. Nowadays, with the help IoT technology, a large amount of data generated from the customer utility can be accurately analyzed and transferred to make correct decisions and give energy conservation advices for customers.
6. Automatic product inspection
In traditional mode, many products don’t have regular inspection, which lead to potential energy consumption. With the support of IoT, product status is monitored continuously by IoT equipment. Thus, product inspection is taken automatically and continually during the utility phase. Undoubtedly, product inspection reduces general energy consumption.
7. Predictive and cooperative maintenance
Based on the continuous flow of information and global Internet platform, product maintenance can be enhanced to a predictive stage on a global basis. By comparing product’s performance through globally networked monitoring systems, prediction of product abnormality, fault diagnostics, product degradation patterns analysis will enhance so that the product will be better prevented from unexpected breakdown in a ubiquitous way. In addition, when a fault occurs, proactive maintenance can be executed more efficiently and more cooperatively through the global platform.
8. Predicting remaining lifetime of parts or components
In most cases, while a product cannot be used, different level components still have its remaining value. Predicting remaining lifetime of parts or components helps to decide what to recycle and what the recycle level should be. IoT technology helps predict the occurrence of breakdown and the relatively accurate remaining lifetime of parts or components by analyzing history data combining with corresponding component ID. This can largely reduce energy consumption in recycle phase.
In addition, Xu et al. [44] has reviewed the advances of IoT in industries, Bi et al. [45] studied the application of IoT in modern enterprise systems, Fan et al. [46] studied IoT-based smart rehabilitation system, and He et al. [47] have researched the application of IoT in the development of vehicular data cloud service.
At present, in manufacturing field, IoT technology is rapidly developing under the support of RFID, sensors, smart technology, and nanotechnology, and is expected to promote interconnection of anything. Then, IoT is helpful to construct a platform for sharing and interconnecting all kinds of manufacturing resources. Coupled with the rapid development of embedded systems and technologies, it provides enabling technologies for realizing the intelligent embedding of physical terminal equipment and the interconnection of M2M (including man-to-man, man-to-machine, and machine-to-machine) in manufacturing.
1.4. The conception of IoT-MS
For better understanding, the definition of IoT-MS will be given at first. IoT-MS is defined as a multisource and real-time manufacturing data-driven manufacturing system, covering procedures of monitor, decision and management from the production orders assigned to the required work in progress or products finished.
IoT-MS consists of two main parts. The first is hardware part, which is responsible for configuring the sensors to capture the multisource and real-time data of the various manufacturing resources by deploying the IoT technologies to traditional manufacturing system. The second is the software part, which wraps a series of decision models, algorithms, and middleware, and is used to monitor, analyze, control, and make decisions for the whole manufacturing system.
1.5. Key features and limitations of IoT-MS
In contrast to current manufacturing systems, the following key features could be seen in the proposed IoT-MS.
Introduce an easy to use and easy to deploy architecture and solution for implementing smart manufacturing in the whole manufacturing systems using the IoTs.
Design the smart framework and models for improving the intelligence of the bottom-level manufacturing resources such as smart station and smart trolley because they are the key to intelligent manufacturing system.
Develop a new decision strategy and method for real-time information-based production scheduling and internal logistics optimization, which can be directly applied to manufacturing system, for example, shop floor, for improving the efficiency.
Present a critical event-based real-time key production performances analysis model, which can be used to actively identify the real-time production exceptions.
Although the proposed architecture, new smart models, strategies, and methods have significant contributions for improving the intelligence and real-time optimization of manufacturing systems, limitations still need to be discussed.
The manufacturing enterprises will invest much money to purchase the IoT hardware and software for capturing the real-time and multisource manufacturing data.
The new technologies of IoT will require the employees to learn specialized knowledge and skills. It is a new challenge for employees.
1.6. Organization of the book
This book systematically introduces the overall architecture, new models, methods, and core technologies related to optimization of manufacturing systems by using the IoTs. It includes 10 chapters, which are organized as follows.
Chapter 1 describes the newly advanced manufacturing technologies and intelligent manufacturing system, and then presents the conception of IoT and IoT-MS, and the challenges of IoT-MS. Chapter 2 proposes an overview of IoT-MS including the architecture, work logic, and relevant core technologies. Chapter 3 describes the model and method of real-time and multisource manufacturing information perception. Chapter 4 presents the framework and the corresponding method of IoT-enabled smart assembly station. Chapter 5 describes the method and algorithm of CC-based manufacturing resources configuration. Chapter 6 describes the new strategy and method for IoT-enabled smart material handling. Chapter 7 presents the models and methods for real-time key production performances monitor. Chapter 8 presents the new strategy and method for real-time information-driven production scheduling. Chapter 9 illustrates the IoT-MS prototype system through a demo. Chapter 10 summarizes the conclusions and points out the future trends.
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