Soujanya Mantravadi | University of Cambridge (original) (raw)

Papers by Soujanya Mantravadi

International journal of production research, Jul 7, 2024

Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023)

This paper explores the implementation of Industrial Internet of Things (IIoT) platforms to addre... more This paper explores the implementation of Industrial Internet of Things (IIoT) platforms to address challenges in adoption due to information technology (IT)/ operational technology (OT) integration difficulties. The study uses a case from food manufacturing and supply. We outline specific requirements for IIoT implementation, leveraging empirical data from Danish food manufacturers and industry reports. By applying the Quality Function Deployment (QFD) method, we assess how 10 Microsoft Azure IoT functionalities (as an illustrative example) align with industry requirements, thereby discussing design considerations. In addition, we demonstrate practical implications in Aalborg University's Industry 4.0 learning factory to present a high-level architecture for IIoT-connected factory systems through Unified Modeling Language (UML). Our study highlights the significance of IT/OT integration for IIoT success and offers a blueprint for efficient data exchange and process control. The findings emphasize the importance of aligning technology choices with industry-specific requirements and provide future research directions for IIoT in brownfield manufacturing. Our results indicate Scalability and Device Connectivity as core functionalities for successful IIoT adoption, with each accounting for high percentages of importance of 19% and 16%, respectively. The paper contributes to Industry 4.0's data integration and enhances food industry operations. Future work will explore additional complexities to enhance IIoT implementation.

IEEE Access, 2020

Manufacturing is facing a host of new security challenges due to the convergence of information t... more Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence.

2018 International Conference on Smart Systems and Technologies (SST), 2018

As per the Industry 4.0 vision, it is well established that ‘Enterprise Integration’ by inter-org... more As per the Industry 4.0 vision, it is well established that ‘Enterprise Integration’ by inter-organizational collaboration in a supply chain can achieve competitive advantage for all the parties. However, not much study is done on the tools at the manufacturer’s end that enable the real-time information sharing in between the integrated enterprises. This paper explores the role of manufacturing information systems (beyond ERP layer) to define the scope/role of smart factories to enhance ‘visibility’ (supply chain visibility). The findings contributed to developing a hypothesis that manufacturing operations management (MOM) systems, especially manufacturing execution systems (MES) of smart factories at ‘manufacturer’ can provide critical product-centric data to the ‘wholesaler’, thus enhancing supply chain performance. This position paper gives insights into the ‘real-time information sharing’ in the fresh food supply chain, by presenting the perspectives of both manufacturer (with MOM systems) and the wholesaler (with needs on real-time production data regarding shipments). Furthermore, it provides a conceptual model illustrating the scope of smart factories towards the manufacturing digitalization. Analysis explored through case example of a Danish meat manufacturer to investigate how MES tool can aid ‘planning’. In addition, the paper also sets the agenda for future research in this area

IFIP Advances in Information and Communication Technology, 2019

Demand information sharing during planning and control of fresh meat production and replenishment... more Demand information sharing during planning and control of fresh meat production and replenishment in franchise supply chain is studied. Main findings are that some demand information is received much later upstream than when created downstream. Horizontal integration of systems in the supply chain allows all parties access to same critical information about store demand and availability in real-time. A conceptual model for horizontal integration in the triadic supply chain, allowing differentiated and timely sharing of information is suggested, to increase service level and reduce waste from over-/under-production.

IEEE Access, 2020

Manufacturing is facing a host of new security challenges due to the convergence of information t... more Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence.

Procedia Manufacturing, 2019

Under the concept of "Industry 4.0", production processes will be pushed to be increasingly inter... more Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization's profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization's value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency.

Proceedings of the 21st International Conference on Enterprise Information Systems, 2019

Smart factory of the future is expected to support interoperability on the shop floor, where info... more Smart factory of the future is expected to support interoperability on the shop floor, where information systems are pivotal in enabling interconnectivity between its physical assets. In this era of digital transformation, manufacturing execution system (MES) is emerging as a critical software tool to support production planning and control while accessing the shop floor data. However, application of MES as an enterprise information system still lacks the decision support capabilities on the shop floor. As an attempt to design intelligent MES, this paper demonstrates one of the artificial intelligence (AI) applications in the manufacturing domain by presenting a decision support mechanism for MES aimed at production coordination. Machine learning (ML) was used to develop an anomaly detection algorithm for multi-agent based MES to facilitate autonomous production execution and process optimization (in this paper switching the machine off after anomaly detection on the production line). Thus, MES executes the 'turning off' of the machine without human intervention. The contribution of the paper includes a concept of next-generation MES that has embedded AI, i.e., a MES system architecture combined with machine learning (ML) technique for multi-agent MES. Future research directions are also put forward in this position paper.

Computers in Industry

Manufacturing is facing challenges in integrating information technology (IT) with operational te... more Manufacturing is facing challenges in integrating information technology (IT) with operational technology (OT) and implementing Industrial Internet of Things (IIoT) concepts in the industry to increase manufacturing flexibility. This paper addresses the research gap in designing and using next-generation manufacturing execution systems (MES)/manufacturing operations management (MOM) in IIoT to improve manufacturing flexibility through reconfigurability. For this, we follow an abductive research design and build on the literature on Industry 4.0 ′ s information architectures and models to propose a framework for building smart factory capabilities. Using the framework, we collect empirical data on MES/MOM implementation objectives for smart factories for six case studies conducted over a 4-year research project in Denmark (2018-2021), primarily through semistructured interviews. Through cross-case analysis, we identify seven dominant themes that capture focus areas for MES/MOM implementation for IT/OT integration. We use these findings to present generalized design recommendations for IIoT-connected MES/MOM to support reconfigurability for Industry 4.0 supply chains. Our findings indicate that despite considerable investments from many companies in Industry 4.0 initiatives such as artificial intelligencebased analytics and digital twins, the industry is not yet in a state to extract the data from all its legacy production equipment. Therefore, we present design recommendations to enable Industry 4.0 supply chains with IIoT-connected MES/MOM by using the data from OT devices. Our analysis helps us conclude that open standards and open application programming interfaces (APIs) are key requirements for enhancing IIoT interconnectivity and interoperability to achieve end-to-end integration in supply chains.

Application of MES/MOM for Industry 4.0 supply chains: A cross-case analysis, 2023

Manufacturing is facing challenges in integrating information technology (IT) with operational te... more Manufacturing is facing challenges in integrating information technology (IT) with operational technology (OT) and implementing Industrial Internet of Things (IIoT) concepts in the industry to increase manufacturing flexibility. This paper addresses the research gap in designing and using next-generation manufacturing execution systems (MES)/manufacturing operations management (MOM) in IIoT to improve manufacturing flexibility through reconfigurability. For this, we follow an abductive research design and build on the literature on Industry 4.0 ′ s information architectures and models to propose a framework for building smart factory capabilities. Using the framework, we collect empirical data on MES/MOM implementation objectives for smart factories for six case studies conducted over a 4-year research project in Denmark (2018-2021), primarily through semistructured interviews. Through cross-case analysis, we identify seven dominant themes that capture focus areas for MES/MOM implementation for IT/OT integration. We use these findings to present generalized design recommendations for IIoT-connected MES/MOM to support reconfigurability for Industry 4.0 supply chains. Our findings indicate that despite considerable investments from many companies in Industry 4.0 initiatives such as artificial intelligencebased analytics and digital twins, the industry is not yet in a state to extract the data from all its legacy production equipment. Therefore, we present design recommendations to enable Industry 4.0 supply chains with IIoT-connected MES/MOM by using the data from OT devices. Our analysis helps us conclude that open standards and open application programming interfaces (APIs) are key requirements for enhancing IIoT interconnectivity and interoperability to achieve end-to-end integration in supply chains.

Procedia Computer Science, 2023

Intelligent Information and Database Systems, 2020

The purpose of this paper is to study an Industry 4.0 scenario of 'technical assistance' and use ... more The purpose of this paper is to study an Industry 4.0 scenario of 'technical assistance' and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer for MES. The chatbot is aimed at production coordination by assisting the shop floor workforce and learn from their inputs, thus acting as an intelligent assistant. We programmed a prototype chatbot as a proof of concept, where the new interface layer provided live updates related to production in natural language and added predictive power to MES. The results indicate that the chatbot interface for MES is beneficial to the shop floor workforce and provides easy information extraction, compared to the traditional search techniques. The paper contributes to the manufacturing information systems field and demonstrates a human-AI collaboration system in a factory. In particular, this paper recommends the manner in which MES based technical assistance systems can be developed for the purpose of easy information retrieval.

Soujanya Mantravadi graduated with an MSc (Eng.) from the KTH Royal Institute of Technology, Swed... more Soujanya Mantravadi graduated with an MSc (Eng.) from the KTH Royal Institute of Technology, Sweden (2015). She completed her master thesis while interning for Alstom in Paris. She studied her bachelor in her hometown, Hyderabad, and received a degree (distinction) in mechanical engineering from JNTU-H, India (2011). She has previously worked as a research analyst at Mordor Intelligence, as a trainee at the Paul Scherrer Institut-ETH Domain, and as an engineer at Amada Co. She was employed as a research assistant at Aalborg University, financed by the Manufacturing Academy of Denmark. Her research focuses on manufacturing digitalization to create solutions based on enterprise information systems. She is a visiting PhD at the Depart

2020 IEEE 18th International Conference on Industrial Informatics (INDIN), 2020

Manufacturing Execution Systems (MES) play an important role in production management. However, m... more Manufacturing Execution Systems (MES) play an important role in production management. However, many MES are either not following the industry standard or not providing high flexibility for small and medium-sized enterprises (SMEs) that are interested in user-defined software and low-cost automation solutions. This paper presents an ISA95 based MES architecture, an open-source evolvable MES that follows an industry standard. It is specifically designed for production management (e.g., production scheduling and execution) in SMEs. We expand this work into three directions. Firstly, we follow the industry standard - ISA95 guideline to identify the key functionalities, activities, and objects of the MES. Secondly, we leverage a model-driven paradigm to show how to design the architecture and data model. To keep it open-source, a business platform Odoo is chosen as it provides various well-designed free ERP modules as a foundation for MES design. Finally, various advanced features of Aa...

As industries are becoming increasingly digitalized, new manufacturing concepts require redesigni... more As industries are becoming increasingly digitalized, new manufacturing concepts require redesigning the information systems architecture. The Smart Production Laboratory is used as a learning factory aimed at exploring new industry 4.0 technologies and for demonstrating Smart Production solutions. The initial Smart Production Laboratory was built on a proprietary software stack. Experimenting with the information systems architecture using proprietary systems has shown to be difficult, which is why we built a complete modular open-source software stack for the Smart Production Laboratory intended to enable high-speed and low-cost development of demonstrators for research, teaching, and innovation. Therefore, the purpose of this research is to capture the development of the software stack and identify the required target architecture for the platform. This is further used for discussing potential future challenges in demonstrating new and innovative Smart Production concepts.

The purpose of this paper is to explore the role of information systems (in smart factories) to s... more The purpose of this paper is to explore the role of information systems (in smart factories) to support the coordination practices in the international manufacturing networks (IMN). The paper attempts to study the usefulness of manufacturing IT tools to enable IMN coordination for optimization of physical distribution. Theoretical propositions made on manufacturing operations management (MOM) systems for IMN coordination (based on the literature study) were empirically examined using two case studies of companies with international manufacturing networks. Based on the qualitative analysis of propositions and empirical findings, the paper identified manufacturing execution systems (MES) to have the potential for achieving IMN coordination goals. As a result, the priorities for developing research agenda in this area to design factories of the future and to achieve Industry 4.0 vision were established. It is the first attempt to analyse the concepts of MES/MOM systems to empirically i...

2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities... more This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic).

This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities... more This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic).

Robotics and Computer-Integrated Manufacturing, 2022

The role of enterprise information systems is becoming increasingly crucial for improving custome... more The role of enterprise information systems is becoming increasingly crucial for improving customer responsiveness in the manufacturing industry. However, manufacturers engaged in mass customization are currently facing challenges related to implementing Industrial Internet of Things (IIoT) concepts of Industry 4.0 in order to increase responsiveness. In this article, we apply the findings from a two-year design science study to establish the role of manufacturing execution systems/manufacturing operations management (MES/MOM) in an IIoT-enabled brownfield manufacturing enterprise. We also present design recommendations for developing next-generation MES/MOM as a strong core to make factories smart and responsive.

First, we analyze the architectural design challenges of MES/MOM in IIoT through a selective literature review. We then present an exploratory case study in which we implement our homegrown MES/MOM data model design based on ISA 95 in Aalborg University's Smart Production Lab, which is a reconfigurable cyber-physical production system. This was achieved through the use of a custom module for the open-source Odoo ERP platform (mainly version 14). Finally, we enrich our case study with three industrial design demonstrators and combine the findings with a quality function deployment (QFD) method to determine design requirements for next-generation IIoT-connected MES/MOM. The results from our QFD analysis indicate that interoperability is the most important characteristic when designing a responsive smart factory, with the highest relative importance of 31% of the eight characteristics we studied.

International journal of production research, Jul 7, 2024

Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023)

This paper explores the implementation of Industrial Internet of Things (IIoT) platforms to addre... more This paper explores the implementation of Industrial Internet of Things (IIoT) platforms to address challenges in adoption due to information technology (IT)/ operational technology (OT) integration difficulties. The study uses a case from food manufacturing and supply. We outline specific requirements for IIoT implementation, leveraging empirical data from Danish food manufacturers and industry reports. By applying the Quality Function Deployment (QFD) method, we assess how 10 Microsoft Azure IoT functionalities (as an illustrative example) align with industry requirements, thereby discussing design considerations. In addition, we demonstrate practical implications in Aalborg University's Industry 4.0 learning factory to present a high-level architecture for IIoT-connected factory systems through Unified Modeling Language (UML). Our study highlights the significance of IT/OT integration for IIoT success and offers a blueprint for efficient data exchange and process control. The findings emphasize the importance of aligning technology choices with industry-specific requirements and provide future research directions for IIoT in brownfield manufacturing. Our results indicate Scalability and Device Connectivity as core functionalities for successful IIoT adoption, with each accounting for high percentages of importance of 19% and 16%, respectively. The paper contributes to Industry 4.0's data integration and enhances food industry operations. Future work will explore additional complexities to enhance IIoT implementation.

IEEE Access, 2020

Manufacturing is facing a host of new security challenges due to the convergence of information t... more Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence.

2018 International Conference on Smart Systems and Technologies (SST), 2018

As per the Industry 4.0 vision, it is well established that ‘Enterprise Integration’ by inter-org... more As per the Industry 4.0 vision, it is well established that ‘Enterprise Integration’ by inter-organizational collaboration in a supply chain can achieve competitive advantage for all the parties. However, not much study is done on the tools at the manufacturer’s end that enable the real-time information sharing in between the integrated enterprises. This paper explores the role of manufacturing information systems (beyond ERP layer) to define the scope/role of smart factories to enhance ‘visibility’ (supply chain visibility). The findings contributed to developing a hypothesis that manufacturing operations management (MOM) systems, especially manufacturing execution systems (MES) of smart factories at ‘manufacturer’ can provide critical product-centric data to the ‘wholesaler’, thus enhancing supply chain performance. This position paper gives insights into the ‘real-time information sharing’ in the fresh food supply chain, by presenting the perspectives of both manufacturer (with MOM systems) and the wholesaler (with needs on real-time production data regarding shipments). Furthermore, it provides a conceptual model illustrating the scope of smart factories towards the manufacturing digitalization. Analysis explored through case example of a Danish meat manufacturer to investigate how MES tool can aid ‘planning’. In addition, the paper also sets the agenda for future research in this area

IFIP Advances in Information and Communication Technology, 2019

Demand information sharing during planning and control of fresh meat production and replenishment... more Demand information sharing during planning and control of fresh meat production and replenishment in franchise supply chain is studied. Main findings are that some demand information is received much later upstream than when created downstream. Horizontal integration of systems in the supply chain allows all parties access to same critical information about store demand and availability in real-time. A conceptual model for horizontal integration in the triadic supply chain, allowing differentiated and timely sharing of information is suggested, to increase service level and reduce waste from over-/under-production.

IEEE Access, 2020

Manufacturing is facing a host of new security challenges due to the convergence of information t... more Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence.

Procedia Manufacturing, 2019

Under the concept of "Industry 4.0", production processes will be pushed to be increasingly inter... more Under the concept of "Industry 4.0", production processes will be pushed to be increasingly interconnected, information based on a real time basis and, necessarily, much more efficient. In this context, capacity optimization goes beyond the traditional aim of capacity maximization, contributing also for organization's profitability and value. Indeed, lean management and continuous improvement approaches suggest capacity optimization instead of maximization. The study of capacity optimization and costing models is an important research topic that deserves contributions from both the practical and theoretical perspectives. This paper presents and discusses a mathematical model for capacity management based on different costing models (ABC and TDABC). A generic model has been developed and it was used to analyze idle capacity and to design strategies towards the maximization of organization's value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity optimization might hide operational inefficiency.

Proceedings of the 21st International Conference on Enterprise Information Systems, 2019

Smart factory of the future is expected to support interoperability on the shop floor, where info... more Smart factory of the future is expected to support interoperability on the shop floor, where information systems are pivotal in enabling interconnectivity between its physical assets. In this era of digital transformation, manufacturing execution system (MES) is emerging as a critical software tool to support production planning and control while accessing the shop floor data. However, application of MES as an enterprise information system still lacks the decision support capabilities on the shop floor. As an attempt to design intelligent MES, this paper demonstrates one of the artificial intelligence (AI) applications in the manufacturing domain by presenting a decision support mechanism for MES aimed at production coordination. Machine learning (ML) was used to develop an anomaly detection algorithm for multi-agent based MES to facilitate autonomous production execution and process optimization (in this paper switching the machine off after anomaly detection on the production line). Thus, MES executes the 'turning off' of the machine without human intervention. The contribution of the paper includes a concept of next-generation MES that has embedded AI, i.e., a MES system architecture combined with machine learning (ML) technique for multi-agent MES. Future research directions are also put forward in this position paper.

Computers in Industry

Manufacturing is facing challenges in integrating information technology (IT) with operational te... more Manufacturing is facing challenges in integrating information technology (IT) with operational technology (OT) and implementing Industrial Internet of Things (IIoT) concepts in the industry to increase manufacturing flexibility. This paper addresses the research gap in designing and using next-generation manufacturing execution systems (MES)/manufacturing operations management (MOM) in IIoT to improve manufacturing flexibility through reconfigurability. For this, we follow an abductive research design and build on the literature on Industry 4.0 ′ s information architectures and models to propose a framework for building smart factory capabilities. Using the framework, we collect empirical data on MES/MOM implementation objectives for smart factories for six case studies conducted over a 4-year research project in Denmark (2018-2021), primarily through semistructured interviews. Through cross-case analysis, we identify seven dominant themes that capture focus areas for MES/MOM implementation for IT/OT integration. We use these findings to present generalized design recommendations for IIoT-connected MES/MOM to support reconfigurability for Industry 4.0 supply chains. Our findings indicate that despite considerable investments from many companies in Industry 4.0 initiatives such as artificial intelligencebased analytics and digital twins, the industry is not yet in a state to extract the data from all its legacy production equipment. Therefore, we present design recommendations to enable Industry 4.0 supply chains with IIoT-connected MES/MOM by using the data from OT devices. Our analysis helps us conclude that open standards and open application programming interfaces (APIs) are key requirements for enhancing IIoT interconnectivity and interoperability to achieve end-to-end integration in supply chains.

Application of MES/MOM for Industry 4.0 supply chains: A cross-case analysis, 2023

Manufacturing is facing challenges in integrating information technology (IT) with operational te... more Manufacturing is facing challenges in integrating information technology (IT) with operational technology (OT) and implementing Industrial Internet of Things (IIoT) concepts in the industry to increase manufacturing flexibility. This paper addresses the research gap in designing and using next-generation manufacturing execution systems (MES)/manufacturing operations management (MOM) in IIoT to improve manufacturing flexibility through reconfigurability. For this, we follow an abductive research design and build on the literature on Industry 4.0 ′ s information architectures and models to propose a framework for building smart factory capabilities. Using the framework, we collect empirical data on MES/MOM implementation objectives for smart factories for six case studies conducted over a 4-year research project in Denmark (2018-2021), primarily through semistructured interviews. Through cross-case analysis, we identify seven dominant themes that capture focus areas for MES/MOM implementation for IT/OT integration. We use these findings to present generalized design recommendations for IIoT-connected MES/MOM to support reconfigurability for Industry 4.0 supply chains. Our findings indicate that despite considerable investments from many companies in Industry 4.0 initiatives such as artificial intelligencebased analytics and digital twins, the industry is not yet in a state to extract the data from all its legacy production equipment. Therefore, we present design recommendations to enable Industry 4.0 supply chains with IIoT-connected MES/MOM by using the data from OT devices. Our analysis helps us conclude that open standards and open application programming interfaces (APIs) are key requirements for enhancing IIoT interconnectivity and interoperability to achieve end-to-end integration in supply chains.

Procedia Computer Science, 2023

Intelligent Information and Database Systems, 2020

The purpose of this paper is to study an Industry 4.0 scenario of 'technical assistance' and use ... more The purpose of this paper is to study an Industry 4.0 scenario of 'technical assistance' and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer for MES. The chatbot is aimed at production coordination by assisting the shop floor workforce and learn from their inputs, thus acting as an intelligent assistant. We programmed a prototype chatbot as a proof of concept, where the new interface layer provided live updates related to production in natural language and added predictive power to MES. The results indicate that the chatbot interface for MES is beneficial to the shop floor workforce and provides easy information extraction, compared to the traditional search techniques. The paper contributes to the manufacturing information systems field and demonstrates a human-AI collaboration system in a factory. In particular, this paper recommends the manner in which MES based technical assistance systems can be developed for the purpose of easy information retrieval.

Soujanya Mantravadi graduated with an MSc (Eng.) from the KTH Royal Institute of Technology, Swed... more Soujanya Mantravadi graduated with an MSc (Eng.) from the KTH Royal Institute of Technology, Sweden (2015). She completed her master thesis while interning for Alstom in Paris. She studied her bachelor in her hometown, Hyderabad, and received a degree (distinction) in mechanical engineering from JNTU-H, India (2011). She has previously worked as a research analyst at Mordor Intelligence, as a trainee at the Paul Scherrer Institut-ETH Domain, and as an engineer at Amada Co. She was employed as a research assistant at Aalborg University, financed by the Manufacturing Academy of Denmark. Her research focuses on manufacturing digitalization to create solutions based on enterprise information systems. She is a visiting PhD at the Depart

2020 IEEE 18th International Conference on Industrial Informatics (INDIN), 2020

Manufacturing Execution Systems (MES) play an important role in production management. However, m... more Manufacturing Execution Systems (MES) play an important role in production management. However, many MES are either not following the industry standard or not providing high flexibility for small and medium-sized enterprises (SMEs) that are interested in user-defined software and low-cost automation solutions. This paper presents an ISA95 based MES architecture, an open-source evolvable MES that follows an industry standard. It is specifically designed for production management (e.g., production scheduling and execution) in SMEs. We expand this work into three directions. Firstly, we follow the industry standard - ISA95 guideline to identify the key functionalities, activities, and objects of the MES. Secondly, we leverage a model-driven paradigm to show how to design the architecture and data model. To keep it open-source, a business platform Odoo is chosen as it provides various well-designed free ERP modules as a foundation for MES design. Finally, various advanced features of Aa...

As industries are becoming increasingly digitalized, new manufacturing concepts require redesigni... more As industries are becoming increasingly digitalized, new manufacturing concepts require redesigning the information systems architecture. The Smart Production Laboratory is used as a learning factory aimed at exploring new industry 4.0 technologies and for demonstrating Smart Production solutions. The initial Smart Production Laboratory was built on a proprietary software stack. Experimenting with the information systems architecture using proprietary systems has shown to be difficult, which is why we built a complete modular open-source software stack for the Smart Production Laboratory intended to enable high-speed and low-cost development of demonstrators for research, teaching, and innovation. Therefore, the purpose of this research is to capture the development of the software stack and identify the required target architecture for the platform. This is further used for discussing potential future challenges in demonstrating new and innovative Smart Production concepts.

The purpose of this paper is to explore the role of information systems (in smart factories) to s... more The purpose of this paper is to explore the role of information systems (in smart factories) to support the coordination practices in the international manufacturing networks (IMN). The paper attempts to study the usefulness of manufacturing IT tools to enable IMN coordination for optimization of physical distribution. Theoretical propositions made on manufacturing operations management (MOM) systems for IMN coordination (based on the literature study) were empirically examined using two case studies of companies with international manufacturing networks. Based on the qualitative analysis of propositions and empirical findings, the paper identified manufacturing execution systems (MES) to have the potential for achieving IMN coordination goals. As a result, the priorities for developing research agenda in this area to design factories of the future and to achieve Industry 4.0 vision were established. It is the first attempt to analyse the concepts of MES/MOM systems to empirically i...

2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)

This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities... more This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic).

This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities... more This paper explores the role of manufacturing execution systems (MES) with ISA 95 functionalities for the reconfigurability in a manufacturing enterprise. The work is aimed at supporting digitalization based on Industry 4.0 and the Industrial Internet of Things (IIoT) concepts. For this, we use the quality function deployment method to link ISA 95 MES functionalities and reconfigurability needs, based on a case example of a cyber-physical factory (AAU Smart Lab). Accordingly, we present a framework to assess reconfigurability for smart factory development. The paper identifies reconfigurability approaches using IIoT connected MES/MOM for tackling severe market disruptions (e.g. the one caused by the ongoing COVID-19 pandemic).

Robotics and Computer-Integrated Manufacturing, 2022

The role of enterprise information systems is becoming increasingly crucial for improving custome... more The role of enterprise information systems is becoming increasingly crucial for improving customer responsiveness in the manufacturing industry. However, manufacturers engaged in mass customization are currently facing challenges related to implementing Industrial Internet of Things (IIoT) concepts of Industry 4.0 in order to increase responsiveness. In this article, we apply the findings from a two-year design science study to establish the role of manufacturing execution systems/manufacturing operations management (MES/MOM) in an IIoT-enabled brownfield manufacturing enterprise. We also present design recommendations for developing next-generation MES/MOM as a strong core to make factories smart and responsive.

First, we analyze the architectural design challenges of MES/MOM in IIoT through a selective literature review. We then present an exploratory case study in which we implement our homegrown MES/MOM data model design based on ISA 95 in Aalborg University's Smart Production Lab, which is a reconfigurable cyber-physical production system. This was achieved through the use of a custom module for the open-source Odoo ERP platform (mainly version 14). Finally, we enrich our case study with three industrial design demonstrators and combine the findings with a quality function deployment (QFD) method to determine design requirements for next-generation IIoT-connected MES/MOM. The results from our QFD analysis indicate that interoperability is the most important characteristic when designing a responsive smart factory, with the highest relative importance of 31% of the eight characteristics we studied.

Springer Lecture Notes in Artificial Intelligence, 2020

The purpose of this paper is to study an Industry 4.0 scenario of ‘technical assistance’ and use ... more The purpose of this paper is to study an Industry 4.0 scenario of ‘technical assistance’ and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer for MES. The chatbot is aimed at production coordination by assisting the shop floor workforce and learn from their inputs, thus acting as an intelligent assistant. We programmed a prototype chatbot as a proof of concept, where the new interface layer provided live updates related to production in natural language and added predictive power to MES. The results indicate that the chatbot interface for MES is beneficial to the shop floor workforce and provides easy information extraction, compared to the traditional search techniques. The paper contributes to the manufacturing information systems field and demonstrates a human-AI collaboration system in a factory. In particular, this paper recommends the manner in which MES based technical assistance systems can be developed for the purpose of easy information retrieval.