Pingyu Jiang

RFID-enabled real-time manufacturing information tracking infrastructure for extended enterprises

In extended enterprises, real-time manufacturing information tracking plays an important role and aims to provide the right information to the right person at the right time in the right format to achieve optimal production management among the involved enterprises. However, many enterprises are caused by lack of timely, accurate and consistent manufacturing data. The laggard information transfer flow and the unmatched information transfer method bring extended enterprises much more uncertainty and unknowingness. This paper proposes a RFID-enabled real-time manufacturing information tracking infrastructure (RTMITI) to address the real-time manufacturing data capturing and manufacturing information processing methods for extended enterprises. Following the proposed infrastructure, the traditional manufacturing resources such as employees, machines and materials are equipped with RFID devices (Readers and Tags) to build the real-time data capturing environment. In addition, a series of manufacturing information processing methods are established to calculate and track the real-time manufacturing information such as real-time manufacturing cost, progress, WIP (Work-in-progress) inventory etc. in parts/assemblies/products at machines/shop floors/enterprises/ extended enterprises levels. Finally, a case study is given to demonstrate the developed framework and corresponding methodologies.

RFID-based smart Kanbans for Just-In-Time manufacturing

This paper proposes a Just-In-Time (JIT) Wireless Manufacturing (WM) framework that is based on RFID (Radio Frequency Identification, RFID) technology and wireless information and communication networks. One of the basic components of this resulting WM solution is the RFID-based smart Kanbans. They are RFID tags and readers attached to shop-floor manufacturing objects such as operators, workstations, containers and inventories. Smart manufacturing objects are traceable to provide real-time information visibility needed for realising JIT manufacturing strategy. Smart Kanbans offer automatic data collection and thus close the manufacturing open loop.

Recognizing control chart patterns with neural network and numerical fitting

Control chart has been widely used to determine whether the state of machining process is stable or not, and pattern recognition technology is often used to automatically judge the changing modes of control chart. It is because that the abnormal patterns of a control chart can reveal the potential problem of machining quality. In order to improve the recognition rate and efficiency of control chart patterns, a neural network-numerical fitting (NN-NF) model is proposed to recognize different control chart patterns. A back propagation (BP) network is first used to recognize control chart patterns preliminarily. And then, numerical fitting method is adopted to estimate the parameters and specific types of the patterns, which is different from the traditional neural network-based control chart pattern recognition methods. Based on this, Monte Carlo simulation is used to generate training and testing data samples. The results of simulated experiment show that training time of this NN-NF model can be reduced. At the same time, the recognition rate can also be improved. At last, a real example is also provided to illustrate the NN-NF model.

e2-MES: an e-service-driven networked manufacturing platform for extended enterprises

Currently, networked manufacturing is regarded as a new manufacturing mode. Extended enterprise is a type of new organizational mode of enterprises for networked manufacturing, which has become the key point for enterprises winning competitions in global markets. Nowadays, many researches and major contributions have been found on networked manufacturing and extended enterprise from academic to industrial areas. However, they mainly focus on partial conceptual/theoretical and practical application fields. How to build the models for networked manufacturing and extended enterprise, satisfactorily control the manufacturing processes at the level of extended enterprise, etc. is becoming a bottleneck. In order to overcome these limitations, on the basis of the philosophy of services driving manufactures, a kind of e-service-driven networked manufacturing model is put forward. In order to implement this model some key enabling techniques are discussed in detail. These include: e-formalizing bottom manufacturing resources; up-streaming manufacturing data; generating an extended enterprise tree that consists of core enterprise and co-enterprises based on products to be manufactured; configuring a networked manufacturing executive system at the level of extended enterprise; scheduling the manufacturing processes by means of the bottom-up strategy; tracking the manufacturing processes in the range of extended enterprise; and collaborating in the manufacturing processes. Furthermore, a test bed called e2-MES is developed with Java web solution. The running example from the industry indicates that the above ideas are feasible and practical.

TeleRP - an Internet web-based solution for remote rapid prototyping service and maintenance

This paper describes a methodology to create an Internet-based infrastructure to service and maintain RP-oriented tele-manufacturing. One of the most important applications of such an infrastructure is to support the closed-loop product development practice. The Java-enabled solution based on WWW/Internet computing model is used to implement the infrastructure. The main functions include the remote part submitting, queuing and monitoring. Under the control of different access competences, manufacturing sites and queues can be maintained, respectively, in distributed locations. A software testbed has been developed in Java to verify the methodology.

Modeling and analyzing of an enterprise collaboration network supported by service-oriented manufacturing

Service-oriented manufacturing is a new manufacturing paradigm and it has appeared in large-scale enterprise clusters over the past few years. In this situation, the increasing service demands from production processes have led to more enterprise collaborations. And the more collaborations among different enterprises have led to the generation of a service-oriented enterprise collaboration network. The purpose of this article is to investigate the clustering characteristics of a service-oriented enterprise collaboration network through an integrating analytic hierarchy process and complex network theory. First, the concept of service-oriented manufacturing is introduced and a logical architecture for implementing the modeling and analyzing of a service-oriented enterprise collaboration network is put forward. Then, the authors establish a topology model of a service-oriented enterprise collaboration network and use an analytic hierarchy process method to estimate the network weights among different manufacturing or service enterprises. Next, service-oriented manufacturing blocks are illustrated and an improved genetic algorithm is adopted to find the optimal blocks. To verify the feasibility and rationality of the proposed method, finally, a case study is presented. It is expected that a reasonable decision of cross-enterprise collaborations and layout would be provided in the present study.

Social manufacturing as a sustainable paradigm for mass individualization

With increasing product personalization and open innovation, the manufacturing paradigm has been transforming to a more decentralized and socialized one. Social manufacturing was proposed as a new paradigm for industry. It extends the crowdsourcing idea to the manufacturing area. By establishing cyber–physical–social connection via decentralized social media, various communities can be formed as complex, dynamic autonomous systems to co-create customized and personalized products and services. This article presents the concept and characteristics of social manufacturing including distributed, adaptive, and self-organization. It also addresses social intelligence in proactive decision-making for organization of socialized resources and producers in the life-cycle of product.

Implementing of a three-phase integrated decision support model for parts machining outsourcing

Parts machining outsourcing (PMO) can be regarded as a strategic weapon to increase product quality and productivity as well as cost cutting in many manufacturing enterprises. However, making an outsourcing decision based on accumulated experience is neither effective nor scientific due to subjective judgement and lack of systematic analysis. Therefore, to systematically help the decision-maker survey and select suppliers to outsource and also to timely achieve the most beneficial portfolio among suppliers in a non-cooperative game structure, this paper proposes an integrated decision support model for PMO using ontology, constraint-based reasoning, fuzzy VIKOR and game theory in three phases, namely supplier prequalification, ultimate selection and order coordination. In the decision-making process, decision factors such as quality, cost and production capability are categorised and put into different phases, respectively, by their characteristics for being measured at a more reasonable method. Finally, a case from a leading printing machinery enterprise is analysed to validate the proposed model. This research is expected to improve the quality and effectiveness of decision-making in PMO.

Modeling and analyzing of an enterprise relationship network in the context of social manufacturing

Under the circumstance of servitization in industry, the increasing service demands of manufacturing processes promote more service-oriented collaborations. Many small and medium enterprises start to provide professional manufacturing services for the product manufacturers, but the disorganization of these distributed enterprises has obstructed the collaboration decision making and led them to inferior positions when bargaining with the core product manufacturers. In this article, a new networked manufacturing mode called social manufacturing is proposed to solve this problem. Its concept and implementary architecture are discussed. Furthermore, a social manufacturing-oriented enterprise relationship network is built to well organize plenty of distributed enterprises. The topology model of the proposed social manufacturing-oriented enterprise relationship network is discussed, and an improved clustering algorithm is proposed to implement the clustering of enterprises based on the enterprise similarity, which would aggregate enterprises into horizontal manufacturing communities for improving their bargaining power, collaborating efficiently and analyzing the manufacturing service industry from a macro view. The core product manufacturers negotiate to select proper enterprises from different horizontal manufacturing communities to form an e-production chain where all the enterprises collaborate to complete the product manufacturing tasks with higher efficiency and minor cost. Moreover, the topological and physical characteristics of social manufacturing-oriented enterprise relationship network are discussed to analyze the enterprise collaborations from a micro view. Finally, an exemplary case is studied to verify the proposed model. It is expected that our work would be beneficial to the research of enterprise organizing and socialized manufacturing resources configuration under social manufacturing environment.

Multi-objective optimization of facility planning for energy intensive companies

Because of the energy shortage and energy price rise, energy efficiency becomes a worldwide hot spot problem. It is not only a problem about cost reduction, but also a great contribute to the environmental protection. However, the energy efficiency was always ignored in the past decades. In order to gain more benefit and become more competitive in the market, energy efficiency should be considered as an essential factor in early planning phase. To overcome these problems, a new approach, which introduces energy efficiency as a key criterion into the planning process, is presented in this article. An energy recovery network is built according to the analysis of process and product demands. Afterwards the energy loss of the whole system, transport performance and space demand are simultaneously taken into account with the purpose of finding good facility planning from both energy and economic aspects. Finally, a practical expanding case is used to validate the correctness and effectiveness of the proposed approach.