An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment

https://doi.org/10.1016/j.ijpe.2014.09.004Get rights and content

Highlights

  • Integrate RFID, cloud technology and intelligent techniques for monitoring and scheduling.

  • RFID and cloud-based architecture improves production transparency and visibility.

  • Intelligent optimization techniques generate effective production scheduling solutions.

  • The architecture is helpful to increase production efficiency, and reduce wastes and costs.

  • Difficulties and lessons in implementation and managerial implications are discussed.

Abstract

Global manufacturing companies have some pressing needs to improve production visibility and decision-making performance by implementing effective production monitoring and scheduling. This paper proposes a radio frequency identification (RFID)-based intelligent decision support system architecture to handle production monitoring and scheduling in a distributed manufacturing environment. A pilot implementation of the architecture is reported in a distributed clothing manufacturing environment. RFID and cloud technologies were integrated for real-time and remote production capture and monitoring. Intelligent optimization techniques were also implemented to generate effective production scheduling solutions. A prototype system with remote monitoring and production scheduling functions was developed and implemented in a distributed manufacturing environment, which demonstrated the effectiveness of the architecture. The proposed architecture has good extensibility and scalability, which can easily be integrated with production decision-making as well as production and logistics operations in the supply chain. Lastly, this paper discusses the difficulties encountered and lessons learned during system implementation and the managerial implications of the proposed architecture.

Introduction

Labor-intensive manufacturing companies in China, such as those specializing in clothing and footwear, face unprecedented global competition and unpredictable demand fluctuations. These companies must determine methods to improve supply chain management. Global uncertainty and business complexity in supply chain operations have recently increased and various leagile supply networks have been proposed (Purvis et al., 2014). “The Smarter Supply Chain of the Future” released in 2010 (Butner, 2010) by IBM Corporation suggests that a smart supply chain is instrumented, interconnected, and intelligent. To possess these core characteristics, information visibility and transparency, as well as decision-making performance in supply chain operations need to be improved.

Companies have developed and implemented various information systems to increase information visibility and transparency (Francis, 2008). The accuracy of production data in these systems relies on the effectiveness of production data capture and monitoring. In labor-intensive manufacturing industries in China, the collection of production data mainly relies on manual recording, barcode scanning, and radio frequency identification (RFID)-based techniques (Wong and Guo, 2014). Manual recording and barcode scanning usually result in incomplete and lagged data, and barcode labels easily become wrinkled or smudged during labor-intensive production. Meanwhile, RFID technology involves a simple process and can be used in these environments because the electronic components of RFID tags are adequately protected inside.

Most information systems for labor-intensive manufacturing are intended to facilitate various business operations and activities. However, these systems fail to automatically provide users with production decisions. Production decision-making, such as production scheduling, relies on the experience and the subjective assessment of production management, which is rarely optimal. Thus, effective production scheduling in labor-intensive manufacturing needs to be investigated.

This study focuses on the production monitoring and scheduling problem faced by distributed labor-intensive manufacturing companies with multiple production plants. This company aims to effectively track and monitor the progress of each production order and determine where and when to produce each order on the basis of real-time production data. An RFID-based intelligent decision support system (RIDSS) architecture is developed in which RFID and cloud technologies are integrated for real-time production capture and remote production monitoring, whereas intelligent optimization techniques are applied to generate effective production scheduling solutions.

The remainder of this paper is organized as follows: Section 2 reviews related studies on RFID-based production monitoring and production scheduling. Section 3 presents the production monitoring and scheduling problem faced by labor-intensive manufacturing companies with multiple production plants. In Section 4, the RIDSS architecture is proposed to address this problem. Section 5 describes the implementation of the RIDSS architecture in a distributed manufacturing company with multiple plants. 6 Evaluation, 7 Discussion present the performance evaluation and discussion of this system. Finally, Section 8 summarizes this paper and suggests future research directions.

Section snippets

Previous studies in RFID-based production monitoring

RFID technology enhances information visibility and traceability in supply chains (Delen et al., 2007). Studies have been conducted on the application of RFID in monitoring production processes (Huang et al., 2007, Lee and Park, 2008) and concluded that RFID technology can improve supply chain performance (Sari, 2010). Effective production decisions are driven by accurate and real-time production data.

Various RFID-based systems have been developed and implemented to track and monitor production

Problem statement

This study aims at proposing an effective RIDSS architecture for production monitoring and scheduling, which is faced by a typical distributed labor-intensive manufacturing company in China. This architecture can be achieved by assisting the production management in monitoring the production progress of each customer order and assigning the production for each order to appropriate production units on a real-time basis. Numerous similar manufacturing companies are operational in China,

RFID-based intelligent decision support system architecture

This section presents the establishment of the RIDSS architecture to implement effective production monitoring and scheduling in a distributed labor-intensive manufacturing environment. Fig. 2 shows the structure of the RIDSS architecture. This architecture uses RFID technology to collect production data from distributed manufacturing environments real-timely while intelligent optimization techniques are implemented to make effective production scheduling decisions. The RIDSS architecture

Prototype system development and implementation

A pilot system was developed to evaluate the effectiveness of the RIDSS architecture proposed in Section 3. A distributed labor-intensive manufacturing company with multiple plants was selected as the pilot company in which this system was evaluated. The pilot manufacturing company is a medium-sized clothing manufacturer producing casual wear and sportswear. The company consists of four production plants located in four different cities. This type of labor-intensive manufacturing company exists

Evaluation

The effectiveness of the proposed architecture is evaluated by the benefits this system provides the pilot company. Prior to the development and implementation of the pilot system in the pilot manufacturing company, manual recordings were used to collect production data. There is a computer operator to input daily job tickets into the computer in each shop floor of sewing department. The production management failed to monitor the production progress of each order in material supplying plants

Cloud-based architecture

A production data capture and monitoring system designed for one plant cannot implement effective integration and sharing of production data collected from different plants. With the development of global manufacturing and in the presence of fierce market competition, this system fails to meet the needs of a distributed global manufacturing network. New and improved architectures are needed to integrate and process a large amount of production data collected from distributed plants and meet

Conclusions

An RIDSS architecture was proposed for effective production monitoring and scheduling in a distributed labor-intensive manufacturing environment on the basis of three different management levels. RFID technology was utilized to collect real-time production records from workstations. An intelligent optimization technique was employed to generate effective production scheduling solutions.

This study is the first to investigate production monitoring and scheduling in distributed labor-intensive

Acknowledgments

The authors are grateful for the constructive comments of the referees on an earlier version of this paper. The authors acknowledge the financial supports from the Sichuan University (Grant nos. SKYB201301 and SKZX2013-DZ07), the National Natural Science Foundation of China (Grant nos. 71302134 and 71371130) and The Hong Kong Polytechnic University (Grant no. YK73).

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