This paper presents the conceptual framework for systematic knowledge representation, storage and... more This paper presents the conceptual framework for systematic knowledge representation, storage and reuse of manufacturing information in a production scenario. This knowledge structure is designed for three levels in a manufacturing set up viz. first at the engineering objects level, second at process and finally at factory level. Virtual engineering object (VEO) deals with knowledge at the individual object/component/machine level while Virtual engineering process (VEP) represents knowledge at the process/operations level. Implementation of VEO and VEP has been already been done. This article proposes the integrated concept and architecture at facility/factory level and we termed it as Virtual Engineering Factory (VEF). It provides access to the complete production history of the factory, which is useful for decision-making activities. Moreover, we propose combined architecture for the extraction of the knowledge from different levels of manufacturing through VEF, VEP and VEO.
Knowledge-based support has become an indispensable part not only to the traditional manufacturin... more Knowledge-based support has become an indispensable part not only to the traditional manufacturing set-ups but also to the new fast-emerging Industry 4.0 scenario. In this regard, successful research has been performed and extensively reported to develop Decisional DNA based knowledge representation models of engineering object and engineering process called Virtual engineering object (VEO), Virtual engineering process (VEP) and Virtual engineering factory (VEF). These models are the virtual representation of manufacturing resources, and with the help of IoT, are capable of capturing the past experience and formal decisions. In this chapter, a complete virtual manufacturing environment is summarized. Furthermore, the scope of this work is explained in the Cyber-Physical Systems (CPS) based Industry 4.0 framework. Four case studies are presented to validate the practical implementation of the proposed concept. In the first case the idea of VEO-VEP-VEF is applied to design an intellig...
Industry 4.0 aims at providing a digital representation of a production landscape, but the challe... more Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.
Industry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It conn... more Industry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It connects physical with digital and allows for better collaboration and access across departments, partners, vendors, product, and people. Consequently, it involves complex designing of highly specialized state of the art technologies. Thus, companies face formidable challenges in the adoption of these new technologies. In this paper, critical components of Industry 4.0, their significance and challenges as identified in the literature are presented. Furthermore, a test case framework for the implementation of Industry 4.0 is proposed. The system covers four layers: decision support, data processing, data acquisition and transmission and sensors. Condition monitoring data from machines and shop floor are captured, stored, organized and visualized in real time. Knowledge representation technique of SOEKS/DDNA is used for doing the semantic analysis of the data, Virtual Engineering Object (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF) are used for creating virtual engineering objects, process and factory respectively, Python and its utility Bokeh is used for visualization. The proposed Industry 4.0 framework will make it possible to gather and analyze data across machines, processes and resources supporting faster, flexible, and more efficient control and production of higher-quality goods at reduced costs.
This paper presents the idea of Smart Virtual Product Development (SVPD) system to support produc... more This paper presents the idea of Smart Virtual Product Development (SVPD) system to support product design. The foundations of the system are based upon smart knowledge management techniques called Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). It enhances the industrial product development process by using the previous experiential knowledge gathered from the formal decisional activities. This experiential knowledge is collected from the group of similar products having some common functions and features. The developed system comprises of three modules: design knowledge management (DKM), manufacturing capability analysis and process planning (MCAPP), and product inspection planning (PIP). The working of design knowledge management module is presented in this study and is validated by using an industrial case study, which suggests that it is capable of capturing and reusing the required design knowledge for material selection process. The developed system has the capability to facilitate decision making and mistake proofing during early stages of product design. It can be beneficial for small and medium enterprises (SMEs) involved in product development.
Modeling an effective mechanism for design and control strategies for the implementation of a fle... more Modeling an effective mechanism for design and control strategies for the implementation of a flexible manufacturing system (FMS) has been a challenge. Consequently, to overcome this issue various techniques have applied in the past but most of these models are effective only for some specific situation or an element of FMS. In this study, the knowledge representation technique of Decisional DNA (DDNA) is applied to FMS to develop a generic model to achieve effective scheduling and manufacturing flexibility. Decisional DNA based Virtual Engineering Objects (VEO) are used as communicating media between machines, equipment and works pieces. The concept of Virtual Engineering Process (VEP) is applied for modeling routing flexibility. VEOs combined with VEPs form FMS-DDNA model, which facilitates in enhancing the performance of FMS, by inducing intelligence based on its own previous experience thus making it practical and smart.
Global Journal of Flexible Systems Management, 2010
A framework for studying the effect of scheduling and manufacturing flexibility on the performanc... more A framework for studying the effect of scheduling and manufacturing flexibility on the performance of flexible manufacturing system has been presented in this paper. Scheduling and manufacturing flexibility are among the many manufacturing strategies considered by the researchers to improve the system performance. In this paper in addition to scheduling and manufacturing flexibility other manufacturing strategies being considered are system configuration, buffer capacity, routing flexibility (manufacturing flexibility), number of pallets, volume of parts, dispatching and sequencing rules (scheduling). Performance of systems is evaluated on make-span time, cost, machine utilization and queue waiting time. The key issues which are addressed in this paper are the impact of different levels of routing flexibility, dispatching and sequencing rules and the increase in number of pallets on the system performance. Simulation results indicate that, with increase in routing flexibility, make-span time decreases. However the maximum benefit is obtained when routing flexibility increased from level 1 to 2. Combinations of sequencing and dispatching rules are identified, which can yield best results for make-span, cost of production, queue waiting time and machine utilization. It is suggested that the proposed methodology can be used in practice for not only setting priorities on specific manufacturing factors but also for highlighting likely factor level combinations that could yield improved shop performance.
This paper presents the concept of smart virtual product development (SVPD) system capable of sup... more This paper presents the concept of smart virtual product development (SVPD) system capable of supporting industrial product development process. It enhances the decision making process during different stages and activities involved in product development i.e. product design, manufacturing, and its inspection planning. The enhancement is achieved by using the explicit knowledge of formal past decision events, which are captured, stored, and recalled in the form of set of experiences. The basic description and principle of the approach are introduced first, and then the porotype version of the system is developed and tested. Working of the design knowledge management module of the system is demonstrated with the case study, which verifies the feasibility of the proposed approach. The presented system successfully supports smart product design and it can play a vital role in Industry 4.0 development.
Cyber Physical Systems and Internet of Things have grown significant attention from industry and ... more Cyber Physical Systems and Internet of Things have grown significant attention from industry and academia during the past decade. The main reason behind this interest is the capabilities of such technologies to revolutionize human life since they appear as seamlessly integrating classical networks, networked objects and people to create more efficient environments. However, enhancing these technologies with intelligent skills becomes an even more interesting and enticing scenario. In this paper, we propose and illustrate through a number of case studies how Decisional DNA, a multi-domain knowledge structure based on experience, can be implemented as a comprehensive embedded knowledge representation for Internet of Things and Cyber Physical Systems. Decisional DNA gathers explicit experiential knowledge based on formal decision events and uses this knowledge to support decision-making processes. The main advantages of using Decisional DNA are as follows: (i) offers a standardized form of the collected knowledge and experience, (ii) provides versatility and dynamicity of the knowledge structure, (iii) stipulates storage of day-today explicit experience in a single configuration, (iv) delivers transportability and shareability of the knowledge, and (v) provides predicting capabilities based on the collected experience. Consequently, test and results of the presented implementation of Decisional DNA case studies support it as a technology that can improve and be applied to the aforementioned technologies enhancing them with intelligence by predicting capabilities and facilitating knowledge engineering processes.
Computer integrated manufacturing (CIM) has enormous benefits as it increases the rate of product... more Computer integrated manufacturing (CIM) has enormous benefits as it increases the rate of production, reduces errors and production waste, and streamlines manufacturing subsystems. However, there are some new challenges related to CIM operating in the Internet of Things/Internet of Data (IoT/ IoD) scenarios associated with Industry 4.0 and cyber-physical systems. The main challenge is to deal with the massive volume of data flowing between various CIM components functioning in virtual settings of IoT. This paper proposes decisional DNAbased knowledge representation framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical CIM. The framework utilizes the concept of virtual engineering object and virtual engineering process for developing knowledge models of various CIM components such as automatic storage and retrieval systems, automatic guided vehicles, robots, and numerically controlled machines. The proposed model is capable of capturing in real time the manufacturing data, information and knowledge at every stage of production, that is, at the object level, the process level, and at the factory level. The significance of this study is that it will support decision-making by reusing the experience, which will not only help in effective real-time data monitoring and processing, but also make CIM system intelligent and ready to function in the virtual Industry 4.0 environment.
Engineering collective intelligence is paramount in current industrial times. This research propo... more Engineering collective intelligence is paramount in current industrial times. This research proposes and presents case studies for collective knowledge structures required in the industry field. Knowledge structures such as Set of Experience and Decisional DNA are extended into more advanced knowledge structures for manufacturing processes. These structures are called Virtual Engineering Object, Virtual Engineering Process and Virtual Engineering Factory. All knowledge structures are implemented and tested in two industrial manufacturing cases of collective knowledge, plus one more case of manufacturing innovation where the case study results proved them as practical standards for engineering collective intelligence.
ABSTRACT In this paper, we present the idea of Smart Innovation Engineering (SIE) System and its ... more ABSTRACT In this paper, we present the idea of Smart Innovation Engineering (SIE) System and its implementation methodology. The SIE system is semiautomatic system that helps in carrying the process of product innovation. It collects the experiential knowledge from the formal decisional events. This experiential knowledge is collected from the group of similar products having some common functions and features. The SIE system behaves like a group of experts in its domain as it collects, captures, and stores the experiential knowledge from similar products as well as reuses this experiential knowledge that ultimately enhances the innovation process of manufactured goods. Moreover, with SIE in hand, entrepreneurs and manufacturing organizations will be able to take proper, enhanced decisions and most importantly at appropriate time. The system gains expertise each time a decision is taken and stored in the form of set of experience that can be used in future for similar queries. Implementation of the SIE system using Set of Experience Knowledge Structure and Decisional DNA for case study suggests that the SIE system is capable of capturing and reusing the innovation-related experiences of the manufactured products. The case study confirmed that the SIE system can be beneficial for entrepreneurs and manufacturing organizations for efficient decision making in the product innovation process.
This paper presents a framework for monitoring, analysing and decision making for a smart manufac... more This paper presents a framework for monitoring, analysing and decision making for a smart manufacturing environment. We maintain that this approach could play a vital role in developing an architecture and implementation of Industry 4.0. The proposed model has features like experience based knowledge representation and semantic analysis of engineering objects and manufacturing process. It is also capable of continuous real time visualization of key performance indicators (KPI's) and supports M2M communications over novel protocols like OPC-UA. Our model covers the industrial manufacturing cycle right from capturing raw data at machine level, converting it into useful information, doing semantics analysis and performs real time KPI visualization.
h i g h l i g h t s • A concept of knowledge based virtual representation for manufacturing proce... more h i g h l i g h t s • A concept of knowledge based virtual representation for manufacturing processes. • Approach to collect, represent, and store experiences as knowledge representation. • Experience based manufacturing DNA is proposed, created, and implemented. • Approach and tools to integrate virtual and physical system.
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF), 2015
The concept of Decisional DNA is decade old. This article introduces the initial idea of Set of E... more The concept of Decisional DNA is decade old. This article introduces the initial idea of Set of Experience Knowledge Structure, its advancement into Decisional DNA, and its potential for real life applications in divers domains. The most current and future research steps into Industry 4.0 are also presented and discussed.
This paper reviews the theories, parallels and variances between Virtual Engineering Object (VEO)... more This paper reviews the theories, parallels and variances between Virtual Engineering Object (VEO) / Virtual Engineering Process (VEP) and Cyber Physical System (CPS). VEO and VEP is an experience based knowledge representation of engineering objects and processes respectively. Cyber-physical systems (CPSs) are the next generation of engineered systems in which computing, communication, and control technologies are tightly integrated. The analysis of basic concepts and implementation method proves that VEO/VEP is a specialized form of CPS and it can play a vital role in the structure building of Industry 4.0. Integration of the two models may result in intelligent machines and advanced analytics.
Service sector has been in focus of academic community for several decades because of its exponen... more Service sector has been in focus of academic community for several decades because of its exponential growth and impact on global economy. Thus, this paper presents theoretical propositions for service quality and customer satisfaction. Former research results and theoretical constructs, referring to definition and dimensions of service quality construct as well as the definition of that fundamental determinant of customer satisfaction construct, are systematically presented. Also, a cause-and-effect relationship between service quality and customer satisfaction and their influence on consumers' purchase habits have long been analysed throughout former research. A systematic review of former research may be significant for service providers in order to compare, improve and adjust their business to customers' needs.
This paper presents the conceptual framework for systematic knowledge representation, storage and... more This paper presents the conceptual framework for systematic knowledge representation, storage and reuse of manufacturing information in a production scenario. This knowledge structure is designed for three levels in a manufacturing set up viz. first at the engineering objects level, second at process and finally at factory level. Virtual engineering object (VEO) deals with knowledge at the individual object/component/machine level while Virtual engineering process (VEP) represents knowledge at the process/operations level. Implementation of VEO and VEP has been already been done. This article proposes the integrated concept and architecture at facility/factory level and we termed it as Virtual Engineering Factory (VEF). It provides access to the complete production history of the factory, which is useful for decision-making activities. Moreover, we propose combined architecture for the extraction of the knowledge from different levels of manufacturing through VEF, VEP and VEO.
Knowledge-based support has become an indispensable part not only to the traditional manufacturin... more Knowledge-based support has become an indispensable part not only to the traditional manufacturing set-ups but also to the new fast-emerging Industry 4.0 scenario. In this regard, successful research has been performed and extensively reported to develop Decisional DNA based knowledge representation models of engineering object and engineering process called Virtual engineering object (VEO), Virtual engineering process (VEP) and Virtual engineering factory (VEF). These models are the virtual representation of manufacturing resources, and with the help of IoT, are capable of capturing the past experience and formal decisions. In this chapter, a complete virtual manufacturing environment is summarized. Furthermore, the scope of this work is explained in the Cyber-Physical Systems (CPS) based Industry 4.0 framework. Four case studies are presented to validate the practical implementation of the proposed concept. In the first case the idea of VEO-VEP-VEF is applied to design an intellig...
Industry 4.0 aims at providing a digital representation of a production landscape, but the challe... more Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.
Industry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It conn... more Industry 4.0 offers a comprehensive, interlinked, and holistic approach to manufacturing. It connects physical with digital and allows for better collaboration and access across departments, partners, vendors, product, and people. Consequently, it involves complex designing of highly specialized state of the art technologies. Thus, companies face formidable challenges in the adoption of these new technologies. In this paper, critical components of Industry 4.0, their significance and challenges as identified in the literature are presented. Furthermore, a test case framework for the implementation of Industry 4.0 is proposed. The system covers four layers: decision support, data processing, data acquisition and transmission and sensors. Condition monitoring data from machines and shop floor are captured, stored, organized and visualized in real time. Knowledge representation technique of SOEKS/DDNA is used for doing the semantic analysis of the data, Virtual Engineering Object (VEO), Virtual Engineering Process (VEP) and Virtual Engineering Factory (VEF) are used for creating virtual engineering objects, process and factory respectively, Python and its utility Bokeh is used for visualization. The proposed Industry 4.0 framework will make it possible to gather and analyze data across machines, processes and resources supporting faster, flexible, and more efficient control and production of higher-quality goods at reduced costs.
This paper presents the idea of Smart Virtual Product Development (SVPD) system to support produc... more This paper presents the idea of Smart Virtual Product Development (SVPD) system to support product design. The foundations of the system are based upon smart knowledge management techniques called Set of Experience Knowledge Structure (SOEKS) and Decisional DNA (DDNA). It enhances the industrial product development process by using the previous experiential knowledge gathered from the formal decisional activities. This experiential knowledge is collected from the group of similar products having some common functions and features. The developed system comprises of three modules: design knowledge management (DKM), manufacturing capability analysis and process planning (MCAPP), and product inspection planning (PIP). The working of design knowledge management module is presented in this study and is validated by using an industrial case study, which suggests that it is capable of capturing and reusing the required design knowledge for material selection process. The developed system has the capability to facilitate decision making and mistake proofing during early stages of product design. It can be beneficial for small and medium enterprises (SMEs) involved in product development.
Modeling an effective mechanism for design and control strategies for the implementation of a fle... more Modeling an effective mechanism for design and control strategies for the implementation of a flexible manufacturing system (FMS) has been a challenge. Consequently, to overcome this issue various techniques have applied in the past but most of these models are effective only for some specific situation or an element of FMS. In this study, the knowledge representation technique of Decisional DNA (DDNA) is applied to FMS to develop a generic model to achieve effective scheduling and manufacturing flexibility. Decisional DNA based Virtual Engineering Objects (VEO) are used as communicating media between machines, equipment and works pieces. The concept of Virtual Engineering Process (VEP) is applied for modeling routing flexibility. VEOs combined with VEPs form FMS-DDNA model, which facilitates in enhancing the performance of FMS, by inducing intelligence based on its own previous experience thus making it practical and smart.
Global Journal of Flexible Systems Management, 2010
A framework for studying the effect of scheduling and manufacturing flexibility on the performanc... more A framework for studying the effect of scheduling and manufacturing flexibility on the performance of flexible manufacturing system has been presented in this paper. Scheduling and manufacturing flexibility are among the many manufacturing strategies considered by the researchers to improve the system performance. In this paper in addition to scheduling and manufacturing flexibility other manufacturing strategies being considered are system configuration, buffer capacity, routing flexibility (manufacturing flexibility), number of pallets, volume of parts, dispatching and sequencing rules (scheduling). Performance of systems is evaluated on make-span time, cost, machine utilization and queue waiting time. The key issues which are addressed in this paper are the impact of different levels of routing flexibility, dispatching and sequencing rules and the increase in number of pallets on the system performance. Simulation results indicate that, with increase in routing flexibility, make-span time decreases. However the maximum benefit is obtained when routing flexibility increased from level 1 to 2. Combinations of sequencing and dispatching rules are identified, which can yield best results for make-span, cost of production, queue waiting time and machine utilization. It is suggested that the proposed methodology can be used in practice for not only setting priorities on specific manufacturing factors but also for highlighting likely factor level combinations that could yield improved shop performance.
This paper presents the concept of smart virtual product development (SVPD) system capable of sup... more This paper presents the concept of smart virtual product development (SVPD) system capable of supporting industrial product development process. It enhances the decision making process during different stages and activities involved in product development i.e. product design, manufacturing, and its inspection planning. The enhancement is achieved by using the explicit knowledge of formal past decision events, which are captured, stored, and recalled in the form of set of experiences. The basic description and principle of the approach are introduced first, and then the porotype version of the system is developed and tested. Working of the design knowledge management module of the system is demonstrated with the case study, which verifies the feasibility of the proposed approach. The presented system successfully supports smart product design and it can play a vital role in Industry 4.0 development.
Cyber Physical Systems and Internet of Things have grown significant attention from industry and ... more Cyber Physical Systems and Internet of Things have grown significant attention from industry and academia during the past decade. The main reason behind this interest is the capabilities of such technologies to revolutionize human life since they appear as seamlessly integrating classical networks, networked objects and people to create more efficient environments. However, enhancing these technologies with intelligent skills becomes an even more interesting and enticing scenario. In this paper, we propose and illustrate through a number of case studies how Decisional DNA, a multi-domain knowledge structure based on experience, can be implemented as a comprehensive embedded knowledge representation for Internet of Things and Cyber Physical Systems. Decisional DNA gathers explicit experiential knowledge based on formal decision events and uses this knowledge to support decision-making processes. The main advantages of using Decisional DNA are as follows: (i) offers a standardized form of the collected knowledge and experience, (ii) provides versatility and dynamicity of the knowledge structure, (iii) stipulates storage of day-today explicit experience in a single configuration, (iv) delivers transportability and shareability of the knowledge, and (v) provides predicting capabilities based on the collected experience. Consequently, test and results of the presented implementation of Decisional DNA case studies support it as a technology that can improve and be applied to the aforementioned technologies enhancing them with intelligence by predicting capabilities and facilitating knowledge engineering processes.
Computer integrated manufacturing (CIM) has enormous benefits as it increases the rate of product... more Computer integrated manufacturing (CIM) has enormous benefits as it increases the rate of production, reduces errors and production waste, and streamlines manufacturing subsystems. However, there are some new challenges related to CIM operating in the Internet of Things/Internet of Data (IoT/ IoD) scenarios associated with Industry 4.0 and cyber-physical systems. The main challenge is to deal with the massive volume of data flowing between various CIM components functioning in virtual settings of IoT. This paper proposes decisional DNAbased knowledge representation framework to manage the storage, analysis, and processing of data, information, and knowledge of a typical CIM. The framework utilizes the concept of virtual engineering object and virtual engineering process for developing knowledge models of various CIM components such as automatic storage and retrieval systems, automatic guided vehicles, robots, and numerically controlled machines. The proposed model is capable of capturing in real time the manufacturing data, information and knowledge at every stage of production, that is, at the object level, the process level, and at the factory level. The significance of this study is that it will support decision-making by reusing the experience, which will not only help in effective real-time data monitoring and processing, but also make CIM system intelligent and ready to function in the virtual Industry 4.0 environment.
Engineering collective intelligence is paramount in current industrial times. This research propo... more Engineering collective intelligence is paramount in current industrial times. This research proposes and presents case studies for collective knowledge structures required in the industry field. Knowledge structures such as Set of Experience and Decisional DNA are extended into more advanced knowledge structures for manufacturing processes. These structures are called Virtual Engineering Object, Virtual Engineering Process and Virtual Engineering Factory. All knowledge structures are implemented and tested in two industrial manufacturing cases of collective knowledge, plus one more case of manufacturing innovation where the case study results proved them as practical standards for engineering collective intelligence.
ABSTRACT In this paper, we present the idea of Smart Innovation Engineering (SIE) System and its ... more ABSTRACT In this paper, we present the idea of Smart Innovation Engineering (SIE) System and its implementation methodology. The SIE system is semiautomatic system that helps in carrying the process of product innovation. It collects the experiential knowledge from the formal decisional events. This experiential knowledge is collected from the group of similar products having some common functions and features. The SIE system behaves like a group of experts in its domain as it collects, captures, and stores the experiential knowledge from similar products as well as reuses this experiential knowledge that ultimately enhances the innovation process of manufactured goods. Moreover, with SIE in hand, entrepreneurs and manufacturing organizations will be able to take proper, enhanced decisions and most importantly at appropriate time. The system gains expertise each time a decision is taken and stored in the form of set of experience that can be used in future for similar queries. Implementation of the SIE system using Set of Experience Knowledge Structure and Decisional DNA for case study suggests that the SIE system is capable of capturing and reusing the innovation-related experiences of the manufactured products. The case study confirmed that the SIE system can be beneficial for entrepreneurs and manufacturing organizations for efficient decision making in the product innovation process.
This paper presents a framework for monitoring, analysing and decision making for a smart manufac... more This paper presents a framework for monitoring, analysing and decision making for a smart manufacturing environment. We maintain that this approach could play a vital role in developing an architecture and implementation of Industry 4.0. The proposed model has features like experience based knowledge representation and semantic analysis of engineering objects and manufacturing process. It is also capable of continuous real time visualization of key performance indicators (KPI's) and supports M2M communications over novel protocols like OPC-UA. Our model covers the industrial manufacturing cycle right from capturing raw data at machine level, converting it into useful information, doing semantics analysis and performs real time KPI visualization.
h i g h l i g h t s • A concept of knowledge based virtual representation for manufacturing proce... more h i g h l i g h t s • A concept of knowledge based virtual representation for manufacturing processes. • Approach to collect, represent, and store experiences as knowledge representation. • Experience based manufacturing DNA is proposed, created, and implemented. • Approach and tools to integrate virtual and physical system.
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF), 2015
The concept of Decisional DNA is decade old. This article introduces the initial idea of Set of E... more The concept of Decisional DNA is decade old. This article introduces the initial idea of Set of Experience Knowledge Structure, its advancement into Decisional DNA, and its potential for real life applications in divers domains. The most current and future research steps into Industry 4.0 are also presented and discussed.
This paper reviews the theories, parallels and variances between Virtual Engineering Object (VEO)... more This paper reviews the theories, parallels and variances between Virtual Engineering Object (VEO) / Virtual Engineering Process (VEP) and Cyber Physical System (CPS). VEO and VEP is an experience based knowledge representation of engineering objects and processes respectively. Cyber-physical systems (CPSs) are the next generation of engineered systems in which computing, communication, and control technologies are tightly integrated. The analysis of basic concepts and implementation method proves that VEO/VEP is a specialized form of CPS and it can play a vital role in the structure building of Industry 4.0. Integration of the two models may result in intelligent machines and advanced analytics.
Service sector has been in focus of academic community for several decades because of its exponen... more Service sector has been in focus of academic community for several decades because of its exponential growth and impact on global economy. Thus, this paper presents theoretical propositions for service quality and customer satisfaction. Former research results and theoretical constructs, referring to definition and dimensions of service quality construct as well as the definition of that fundamental determinant of customer satisfaction construct, are systematically presented. Also, a cause-and-effect relationship between service quality and customer satisfaction and their influence on consumers' purchase habits have long been analysed throughout former research. A systematic review of former research may be significant for service providers in order to compare, improve and adjust their business to customers' needs.
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Papers by Imran Shafiq