C HAPTER 13
3. Effect of the Industry 4.0 on ERP Systems
ERP systems have a complex software environment which includes different layers. An ERP software includes a database design and a database layer in order to keep different numbers of data from the system. The database can only access by core business logics such as security applications, firewalls that is provided by server level. The business functions such as finance, marketing, production etc. are modeled as applications at the business applications layer. Finally, end-users are accessed to the system by using user interfaces at the end-user layer. The whole architecture is summarized in the Figure 3.
Industrialization is the paradigm that covers progress on producing materials in better conditions. The changes in industrialization has been called “industrial revolutions” and the first industrial revolution is the development on mechanization, the second industrial revolution is the development on electrical energy, the third industrial revolution is the development on automation and digitalization and the fourth industrial revolution is the development on internet and smart objects (Lasi et al. 2014). The production environment is changing day by day in order to achieve a more productive manufacturing environment. The 4th industrial revolution provides more efficient production systems by connecting devices and equipment together via internet. The evolutions of Industry 4.0 are depicted in Figure 4.
Most of Industry 4.0 related technologies influence the new ERP systems at different levels of obtaining, analyzing and mining the data. For example, the cloud computing technologies and the big data technologies make a great improvement on the ERP software capabilities due to obtaining data from the source automatically. Similarly IoT devices make easier data integration with the ERP systems. Moreover, artificial intelligence and the autonomous robots provide to gain inferences from the ERP systems and achieving business intelligence.
In classical approach the corporate data are stored in the SCADA system which is used as data acquisition systems. The data are analyzed in order to achieve manufacturing tracing or better decision making systems. Finally, in the knowledge level, ERP systems are implemented to increase integration between processes and data. Figure 5 shows the relationship between classical systems and Industry 4.0 technologies.
3.1 Data Level
In the data level, obtaining data from the source and storing it is an important extension point of the future ERP systems.
IoT and cloud technologies of industry 4.0 are suitable for this aim. RFID (Radio Frequency Identification) systems are one of the equipment that can acquire data from the source. RFID technologies can make variety of processes more visible such as receiving, replenishment, order fulfillment, shipping and product tracking (Angeles 2005). RFID technologies are incorporated by IoT devices which changes the information acquiring processes of the ERP systems. This will lead to the IoT and ERP integration becoming mandatory in future factories. These integrations will reinforce the ERP systems into
Business Application Servers
Core Business Logic
DB DB DB
Fig. 3: Software Architecture of ERP systems.
18th Century
INDUSTRY 2.0
Mass production INDUSTRY 3.0
Assembly line Automation
Electrical energy
THE STAGES OF INDUSTRY 4.0
Computers and
Electronics INDUSTRY 1.0
Mechanisation
Water power
Steam power
19th Century 20th Century
21th Century
INDUSTRY 4.0
Cyber physical systems
Internet of things
Smart devices
Fig. 4: The evolutions of Industry 4.0.
interfaces of customer, human-machine, partner, and the employee with different manners such as mobile apps, predictive models, automatic data exchange to achieve total cost ownership (Ranjan et al. 2017).
Cloud ERP systems are the new trends in the ERP industry. Cloud computing may define the hardware and software systems that ensure the services for using applications over Internet (Armbrust et al. 2010). Cloud computing provide to use the applications as platform free and it enables ERP systems more capability. For enhanced capability of cloud ERP systems strategic decisions on how firms could effectively respond to market dynamism are required (Gupta et al. 2019).
Comment [AD2]:Aq: unclear what this sentence is trying to state
182 Logistics 4.0: Digital Transformation of Supply Chain Management
STANDARD ARCHITECTURE INDUSTRIAL INTERNET OF THINGS
Enterprise Resource Planning (ERP)
Supervisory Control and Data Acquisition (SCADA)
Manufacturing Execution System (MES)
INDUSTRY 4.0
Device Device Device Device
Device Device Device Device
APP APP APP
APP Communication
Infrastructure
Fig. 5: The change on different level of data by Industry 4.0.
Cloud systems changes ERP software to ERP service by using Software As A Service (SAAS) architecture. There are lots of important factors making decision on the SAAS architecture and the important ones are given as follows (Johansson and Ruivo 2013): costs, security, availability, usability, implementation, ubiquity, flexibility, compatibility, analytics and best-practices. Web based systems have a lot of flexibility, compatibility, analytics (due to the hardware power of cloud systems), ease of implementation, availability and usability.
3.2 Information Level
In the information level, acquired data have been analyzed and some inferences have been constituted. Artificial intelligence is one of the inference methods for this aim. Artificial intelligence is aimed to develop software systems which simulate the human being behaviors such as learning, reasoning and natural language communication (O’Hare et al. 1996). The artificial intelligent techniques are easily implemented to different decisions on the ERP system such as scheduling (Rojek and Jagodziński 2012; De Toni 1996), time-series forecasting (Doganis et al. 2006), logistics (Tan 2001), and inventory decisions (Roy et al. 1997; Farhat et al. 2017).
Among from other artificial intelligence techniques, distributed computation makes a great enhancement on the ERP systems due to the fact that number of different decision makers need to decide independently in most of decisions related with ERP systems. Agent based systems are the software that decide autonomously on a system in a distributed manner.
Agent based systems have lots of real-world applications that guide to fill the gap into transformation from classical systems to Industry 4.0 facilities (Adeyeri et al. 2015). Agent based systems can make a variety of artificial intelligent applications on the ERP systems such as supplier selection (Li et al. 2018) and scheduling (Manupati et al. 2016). Furthermore, the agent based systems can easily handle system administration tools of ERP such as virtual enterprise systems (Sadigh et al. 2017), increasing functionalities (Mesbahi et al. 2015), the systems own data structures (Vidoni and Vecchietti 2015), and even conducting maintenance (Kwon and Lee 2001).
3.3 Knowledge Level
Intelligent robots are new manufacturing models for the new technological era. Robots need to make acceleration, flow, and some operations due to the fact that they should process and analyze lots of raw data obtained from the different sources such as gyro, force, image and sound sensors (Sakagami et al. 2002). Intelligent robots need cloud systems and big data applications for this amount of raw data (Anton et al. 2020). Robots are important to achieve a sustainable manufacturing environment which includes redesigning, reusing, remanufacturing, recovering, recycling and reducing operations (Bi et al. 2015).
Smart facilities are the future factory concept that connects intelligent manufacturing, planning and autonomous decision-making. Therefore, the smart factory model is primarily aimed at facilitating and ensuring the availability of all relevant information for real-time storage, which will be possible through the integration between all elements in the value chain (Majeed and Rupasinghe 2017).