IoT-based production logistics and supply chain system – Part 1. Modeling IoT-based manufacturing supply chain
| Published date | 05 February 2018 |
| Pages | 65-95 |
| Date | 05 February 2018 |
| DOI | https://doi.org/10.1108/IMDS-11-2016-0503 |
| Author | Mengru Tu,Ming K. Lim,Ming-Fang Yang |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
IoT-based production logistics
and supply chain system –Part 1
Modeling IoT-based manufacturing
supply chain
Mengru Tu
Department of Transportation Science,
National Taiwan Ocean University, Keelung, Taiwan
Ming K. Lim
Centre for Business in Society,
Coventry University, Coventry, UK, and
Ming-Fang Yang
Department of Transportation Science,
National Taiwan Ocean University, Keelung, Taiwan
Abstract
Purpose –The lack of reference architecture for Internet of Things (IoT) modeling impedes the successful
design and implementation of an IoT-based production logistics and supply chain system (PLSCS).
The authors present this study in two parts to address this research issue. Part A proposes a unified IoT
modeling framework to model the dynamics of distributed IoT processes, IoT devices, and IoT objects.
The models of the framework can be leveraged to support the implementation architecture of an IoT-based
PLSCS. The second part (Part B) of this study extends the discussion of implementation architecture proposed
in Part A. Part B presents an IoT-based cyber-physical system framework and evaluates its performance.
The paper aims to discuss this issue.
Design/methodology/approach –This paper adopts a design research approach, using ontology, process
analysis, and Petri net modeling scheme to support IoT system modeling.
Findings –The proposed IoT system-modeling approach reduces the complexity of system development
and increases system portability for IoT-based PLSCS. The IoT design models generated from the modeling
can also be transformed to implementation logic.
Practical implications –The proposed IoT system-modeling framework and the implementation
architecture can be used to develop an IoT-based PLSCS in the real industrial setting. The proposed modeling
methods can be applied to many discrete manufacturing industries.
Originality/value –The IoT modeling framework developed in this study is the first in this field which
decomposes IoT system design into ontology-, process-, and object-modeling layers. A novel implementation
architecture also proposed to transform above IoT system design models into implementation logic.
The developed prototype system can track product and different parts of the same product along a
manufacturing supply chain.
Keywords Internet of Things, RFID, Petri net, Manufacturing supply chain, Production logistics
Paper type Research paper
1. Introduction
The Internet of Things (IoT) is envisioned as creating a world whereby every object
has a digital identity and can connect to a data network (Gershenfeld et al., 2004).
Radio-frequency identification (RFID) technology, which can be used to give digital
identity to the objects, has recently been widely adopted by various industries, such as
manufacturing, retails, and pharmaceuticals. Successful applications of RFID in tracking
objects, people, and animals contribute to the realization of the vision of IoT for a global
infrastructure of networked physical objects (Kortuem et al., 2010). More specifically, the
IoT enters our daily lives through a wireless network of uniquely identifiable objects
Industrial Management & Data
Systems
Vol. 118 No. 1, 2018
pp. 65-95
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-11-2016-0503
Received 20 November 2016
Revised 18 May 2017
Accepted 24 June 2017
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
65
IoT-based
PLSCS –Part 1
(Welbourne et al., 2009); it extends the internet to physical objects and promises a smart,
highly networked world (Quack et al., 2008). Businesses could employ IoT technology to
change their business practices along with their trade partners to improve supply
chain integration and efficiency. IoT applications enable real-time visibility of products
across the global manufacturing supply chain and bring responsiveness and agility to
business operations. IoT-based applications also aid firms in reducing data latency,
analysis latency, and decision latency (Hackathorn, 2003). In addition to automatic
object identification, the IoT comprises a global internet-based information architecture
facilitating the exchange of goods and services in global supply chain networks
(Liu and Sun, 2011). Thus, the IoT will greatly shape the evolution of production logistics
(PL) in manufacturing and supply chain operation in numerous industries at a global
scale. For manufacturing firms, PL denotes the logistics activities related to material
transfer between production steps and accounts for nearly 95 percent execution time of
the entire manufacturing process (Qu et al., 2016). The PL process is not just limited to
intra-firm scope, but should also extend to inter-firm scope, involving material supply,
material warehousing, manufacturing, product warehousing, and product consumption
among suppliers, manufacturers, and retailers (Qu et al., 2016). In light of the scope of PL,
the dynamics in a manufacturing supply chain network should be included in the
study of a PL system. IoT data come from many sources and may contain discrete
(ex. RFID event), continuous data (ex. wireless sensor data), or both. In this research, we
only focus on the discrete data because many IoT applications in PL and supply chain
mainly concern with discrete information such as production pedigree or product life
cycle information. Therefore, we consider an IoT-based production logistics and supply
chain system (hereafter abbreviated as “IoT-based PLSCS”) a discrete event system
(DES) in this study.
The boundary of many manufacturing supply chains is not confined within a single
company but extends to several firms along with a supply chain. The most commonly used
IoT information architecture currently available for supply chain applications is the
EPCglobal Network (Liu and Sun, 2011). The basic infrastructure of an IoT-enabled supply
chain comprises the EPC and EPCglobal Network (EPCglobal, 2007, 2010). The EPC is an
international, unambiguous code for designating physical goods. The EPC and EPCglobal
Network architecture is created to ensure RFID interoperability in supply chain-wide
applications (Thiesse et al., 2009). Figure 1 describes the EPCglobal Network architecture
(EPCglobal, 2007, 2010). The EPC is an identification scheme for universally and uniquely
identifying objects that have EPC tags. RFID readers installed in various manufacturing
and supply chain settings can retrieve product data stored in the tags and supply chain
members can query, update, or exchange information in real time through the EPCglobal
Network (Bo and Guangwen, 2009). The application-level event (ALE) is the middleware in
the architecture, which is a program module or service facilitating IoT event processing and
information exchange between the RFID readers and enterprise information systems
(Bo and Guangwen, 2009; EPCglobal, 2010). As illustrated in Figure 1, the ALE middleware
filters RFID data from RFID reader and generates EPC Information Services (EPCIS) events,
which contains 4W (what, where, when, and why) information relevant to RFID-tagged
products passing through a supply chain read point. The sheer amount of raw data
generated by even a few readers can easily cause an unacceptable load on corporate
networks and systems. Therefore, a middleware layer is required to filter, aggregate, and
associate the data collected from readers on the network’s edge (Thiesse et al., 2009).
3EPC standards offer total supply chain visibility, providing the ability to know exactly
where products are located and why. Central to this concept is the EPCIS standard. EPCIS
consists of a set of networking and data-sharing standards which enable companies to share
information among supply chain partners; this information contains not only serial numbers
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