Dimitris MOURTZIS | University of Patras (original) (raw)

Papers by Dimitris MOURTZIS

Over the past decades, automation industry has seen a major shift from traditional, hard-tooled l... more Over the past decades, automation industry has seen a major shift from traditional, hard-tooled lines to reconfigurable and reprogrammable robotic cells. Robots have added increasing value to the industry with special focus on robotic arms which enable many repetitive tasks to be carried out with high repeatability, reliability, flexibility, and speed. Grasping, carrying and placement of objects are the basic capabilities of robotic arms. However, with the integration of new technologies the capabilities, of robotic arms can be extended. As such, grippers being an essential component of robots play an important role in many handling tasks since they serve as end-of-arm tools. The aim of this paper is to propose a new end effector design, which is integrated with a sensing system, for improving the adaptivity and flexibility of a robotic cell in comparison with the State-of-the-Market end effector solutions. The proposed design is used to extend this research work and to develop an intelligent end effector based on the implementation of a Machine Vision algorithm, for the recognition of the part, the gripper, and 3D scanning the produced part. The recognition of the part is essential in order for the robot to grasp the object appropriately and facilitate the machining process. The 3D scanning of the part geometry will be utilized for CAD comparison versus the original drawings. Finally, based on the Finite Element Analysis (FEA) and the topology optimization, a reduction of the material used for the 3D printing of the gripper has been reduced by 19.57%.

The main characteristic of the Industry 4.0 era is the increased digitalization and complexity of... more The main characteristic of the Industry 4.0 era is the increased digitalization and complexity of manufacturing systems. However, for the successful shift to digitalization, the need for a new generation of engineers, the Generation 4.0 Engineers, emerges. Hence, academia must provide the Generation 4.0 engineers with enhanced skills, competencies and hands-on experience as well. A promising solution is the adoption of the Learning Factory paradigm. Therefore, in this paper, the design and development of a highly automated, and flexible manufacturing cell is proposed under the Learning Factory framework. Participating students are divided into groups, responsible for designing and developing one of the system components and thereupon combined so as to form the final solution. The practical implementation of the proposed concept is realized through the case of a manufacturing cell, comprising a 3D-printer, a robotic arm and a CNC milling machine. Consequently, the students are divided into three groups, responsible for the cell layout, the background algorithm, and the multipurpose gripper. The proposed cell has been tested in vitro, in order to assess the skills, the competencies as well as the hands-on experience each of the students has acquired from the completion of the above-mentioned project.

Decision making at the shop floor level has become more complex than ever before due to the massi... more Decision making at the shop floor level has become more complex than ever before due to the massive growth in available data. The increasing market demands, concerning product quality and delivery times, make critical judgement and decision-making crucial requirements of the modern manufacturing problems. Human decision making has become insufficient and struggles to achieve manufacturing goals. Cutting edge technologies like the Internet of Things (IoT) and Cyber Physical Systems (CPS), that are the cornerstones of the Industry 4.0 smart factories, can contribute to efficient decision making. Therefore, more accurate and improved critical decisions can be achieved for the current as well as for the future status of a manufacturing system. Furthermore, production scheduling is one of the main issues that engineers have to address. The decision support tools of the Industry 4.0 era contribute to effective production scheduling, while considering a larger amount of data and constraints than ever before. This research work proposes a production scheduling method, that uses past and near real-time data to check resource and task status, providing insight to production engineers and enabling enhanced decision making. The results are validated in a structural steelwork industry shop case study.

Industry 4.0 enables the transition of traditional manufacturing models to the digitalized paradi... more Industry 4.0 enables the transition of traditional manufacturing models to the digitalized paradigm, creating significant economic opportunities through market reshaping. Scheduling is a key field of manufacturing systems. Academia and industry are closely collaborating for producing enhanced solutions, taking advantage of multiple criteria. Initially, the scheduling problem was dealt with more simplistic methods resulting in static solutions; however, with the evolution of digital technologies, scheduling became more dynamic to the company's environmental changes. As Information and Communication Technologies (ICT) became mainstream and systems were integrated, rescheduling and adaptive scheduling became the cornerstones of Smart Manufacturing. These technologies have been further advanced to yield more reliable results in a shorter period of time. The efficient design, planning, and operation of manufacturing systems and networks can be achieved with the adoption of cyber physical systems (CPS) in conjunction with the Internet of Things (IoT) and cloud computing. The transition to Smart Manufacturing is achieved with the adoption of cutting-edge digital technologies and the integration state-of-the-art manufacturing assets. Consequently, this chapter presents an opportunity for tracking the evolution of scheduling techniques during the last decade, as well as for extracting insightful and meaningful inferences from the application of innovative solutions in industrial use cases.

In the competitive era of industrial automation, enterprises are struggling to maintain their com... more In the competitive era of industrial automation, enterprises are struggling to maintain their competitiveness, through modernization of their manufacturing systems, while trying to meet market demands. Modernization of manufacturing systems refers to the replacement of manufacturing equipment with state-of-the-art machinery. A good alternative is the act of retrofitting existing machinery, by adding new features. The challenge arising by retrofitting is the selection of the suitable features to be added. This paper presents a conceptual framework to assist the decision-making process, supported by an online network and based on Augmented Reality for retrofitting and recycling machinery, aiming at increasing components' lifecycle.

Integrating the Internet of Things in Industry 4.0 demands the combination of existing practises ... more Integrating the Internet of Things in Industry 4.0 demands the combination of existing practises with new technologies. Augmented Reality (AR) is a cutting-edge technology of the new manufacturing era. The fourth industrial revolution challenges and AR technology advances, promise to improve productiveness, working quality, user experience and allow better use of resources. AR combined with mass customization could fulfil rising market demands and customer functional requirements. This work presents the development of an AR application to integrate customers in the designing process with product customization. The application is to be validated and used in the industry of Robotic Cell Manufacturing.

This work analyses the required expertise knowledge for the European workforce under the implemen... more This work analyses the required expertise knowledge for the European workforce under the implementation spectrum of the technologies from Industry4.0. The advancement of the conventional manufacturing technologies with complementary monitoring and control systems combined with the rapid growth of unconventional manufacturing technologies, calls for the equivalent advancement in the workforce's expertise. The Industry's 4.0 skills are mapped and categorized based on the knowledge requirements derived from the major technologies involved. The competences' categorization is what further determines the Professional Profiles and skills requirements for the Industry4.0. As Additive Manufacturing is one of the most significant manufacturing technologies implemented from Industry4.0 a case study for the required AM skills is performed. The outcome of this work indicates that the AM Professional Profile is a multi-dimensional quantity with multiple competence units that require validation and further evaluation in order to meet the skills requirements imposed by the industry.

Management platforms. The integration of such technologies, employing information that is generat... more Management platforms. The integration of such technologies, employing information that is generated during different phases of a product lifecycle, may lead to the better utilization and optimization of existing resources, such as labor, materials, energy, and equipment, as well as to the development of products of higher quality and performance in a sustainable manner. Considering the continuous growth of available computational power, the proliferation of cloud-based platforms, the cost-efficient development and utilization of once prohibitively expensive equipment, such as robotic systems (stationary, mobile, collaborative, and wearable), advanced sensors, and 3D printers, there will be a time when engineers will be able to transform the requirements pertaining to a new product to detailed production, supply chain, and product lifecycle management configurations in a very accurate manner, exploring diverse demand and production scenarios. Engineers would at some point be capable of identifying very fast, perhaps in a fully automated and intuitive way, what the product design would look like, which resources would be needed for developing the product and how they should be configured, who would be supplying parts, equipment, and services, how the product could be repaired and updated, and how it could be recycled when reaching its end of life. Although products and manufacturing processes are typically quite complex and are often associated with a high degree of uncertainty, it is expected that the availability of more information will lead to the generation of structured product development knowledge and models, which will make their way in tightly integrated digital manufacturing platforms, thus enabling the faster and overall more efficient development of products and services. However, the first demonstrations of Industry 4.0 principles and technologies are already here and will pave the way towards further developments in manufacturing. This book includes 13 papers that discuss how the Industry 4.0 paradigm may be applied in real engineering and manufacturing cases. The topics covered span a series of diverse areas related to: product design and development [1-3], manufacturing systems and operations [4-8], process engineering [9,10], and Industry 4.0 technologies review and realization [11-13].

In today's business environment, the trend towards more product variety and customization is unbr... more In today's business environment, the trend towards more product variety and customization is unbroken. Due to this development, the need of agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach.

The currently applied maintenance strategies, including Reactive and Preventive maintenance can b... more The currently applied maintenance strategies, including Reactive and Preventive maintenance can be considered obsolete. The constant improvements in Information and Communication Technologies as well as in Digital Technologies along with the increase of computational power, have facilitated the development of new Artificial Intelligence algorithms to integrate cognition in computational systems. This trend is posing a great challenge for engineers, as such developments will enable the creation of robust systems that can monitor the current status of the machines and by extension to predict unforeseeable situations. Furthermore, Smart Computers will be capable of examining all possible scenarios and suggest viable solutions in a fraction of time compared to humans. Therefore, in this paper, the modelling, design and development of a Predictive Maintenance and Remote Monitoring system are proposed, based on the utilization of Artificial Intelligence algorithms for data acquisition, fusion, and postprocessing. In addition to that, the proposed framework will integrate a Mixed Reality application for the intuitive visualization of the data, that will ultimately facilitate production and maintenance engineers to monitor the condition of the machines, and most importantly to get an accurate prediction of the oncoming failures.

A smart mobility platform aiding in guidance of disabled people is a concept that can facilitate ... more A smart mobility platform aiding in guidance of disabled people is a concept that can facilitate people's everyday life. However, design and manufacturing of such a system faces many issues in terms of agility in design, implementation and usability verification. To this end, the concept of Product-Service System (PSS) seems to be the solution; being an emerging concept oriented towards the dematerialisation of the economy, meeting also the requirement of manufacturing industries to cope with the radical changes in the global market. In this study, the development of a context awareness and path planning system under the prism of PSSs is examined. This module is considered to be promoted as a pay per service unit that can be implemented in different operational scenarios and environments. The key objective is to deliver the obstacle avoidance and path planning functionality and add value to the customer, but at the same keep the production lean and flexible. To this end, Round Robin parts are presented, taking into account mounts and jigs for controllers dealing with supervised machine learning techniques and path planning, lightweight system-of-sensors and structural integrity of the module. The concept evaluation is outlined through a case study based on the integration of the system in a smart mobility platform to provide autonomous mobility. The mobility platform is expected to operate within a predefined area, characterized by a complex environment.

During the last decade, the technologies related to electric vehicles (EVs) have captured both sc... more During the last decade, the technologies related to electric vehicles (EVs) have captured both scientific and industrial interest. Specifically, the subject of the smart charging of EVs has gained significant attention, as it facilitates the managed charging of EVs to reduce disturbances to the power grid. Despite the presence of an extended literature on the topic, the implementation of a framework that allows flexibility in the definition of the decision-making objectives, along with user-defined criteria is still a challenge. Towards addressing this challenge, a framework for the smart charging of EVs is presented in this paper. The framework consists of a heuristic algorithm that facilitates the charge scheduling within a charging station (CS), and the analytic hierarchy process (AHP) to support the driver of the EV selecting the most appropriate charging station based on their needs of transportation and personal preferences. The communications are facilitated by the Open Platform Communications-Unified Architecture (OPC-UA) standard. For the selection of the scheduling algorithm, the genetic algorithm and particle swarm optimisation have been evaluated, where the latter had better performance. The performance of the charge scheduling is evaluated, in various charging tasks, compared to the exhaustive search for small problems.

Under the Industry 4.0 framework, a plethora of digital technologies and techniques has been intr... more Under the Industry 4.0 framework, a plethora of digital technologies and techniques has been introduced in the Manufacturing domain. Machine tools must become more intelligent, in order to create a network of fully connected machines. By extension, this will lead to the creation of the Industrial Internet of Things (IIoT). Although these technologies provide for increased functionality of the manufacturing equipment, there are certain issues/implications, refraining engineers from integrating such technologies in the production. Therefore, in this paper, the results of a systematic literature review are presented and discussed, including the horizontal and vertical integration of such digital technologies. The contribution of this paper extends to the recognition of the opportunities emerging as well as the identified implications from a practical implementation point of view.

Industries nowadays try their best to remain competitive in a manufacturing world that undergoes ... more Industries nowadays try their best to remain competitive in a manufacturing world that undergoes a digital transformation driven by smart technology and connected devices. Profit margins quickly shift from products to services, and thus the manufacturing sector industries try to shift from offering products to offering industrial product service systems (IPSS) in order to keep up to date and ensure their market position and economic success. IPSS is a well-rounded solution consisting of the tangible part which is the product and an intangible one being the service. IPSS are efficient and beneficiary not only for the provider but also for the user and even the environment. IPSS is not a simple process of adding services to traditional products but a rather more complex integration process of the mechanical product, sensors, and IoT and software, which are coupled with supportive systems (resources and infrastructures) and the involvement of heterogeneous stakeholders. Due to the high complexity involved in the development and production process of IPSS, tools for IPSS production planning and installation in a dynamic and collaborative environment are extremely essential for manufacturing firms, but they are however absent. In this paper, a methodology for conducting resource planning for the production and installation of IPSS is proposed, and according to this, the architecture of a cloud-based tool is developed. A real-life pilot case from a laser and sheet metal machinery production industry is presented where the developed tool was tested and validated upon its results.

As the industrial requirements change at a rapid pace due to the drastic evolution of technology,... more As the industrial requirements change at a rapid pace due to the drastic evolution of technology, the necessity of quickly investigating potential system alternatives towards a more efficient manufacturing system design arises more intensely than ever. Manufacturing systems simulation has proven to be a powerful tool for designing and evaluating a manufacturing system due to its low cost, quick analysis, low risk and meaningful insight that it may provide, improving thus the understanding of the influence of each component. Simulation comprises an indispensable set of IT tools and methods for the successful implementation of digital manufacturing. It allows experimentation and validation of product, process, and system design and configuration. This paper investigates the major historical milestones in the evolution of manufacturing systems simulation technologies and examines recent industrial and research approaches in key fields of manufacturing. It describes how the urge towards digitalisation of manufacturing in the context of the 4th Industrial revolution has shaped simulation in the design and operation of manufacturing systems and reviews the new approaches that have arisen in the literature. Particular focus is given to technologies in the digitalised factories of the future that are gaining ground in industrial applications simulation, offering multiple advantages.

The advent of Electric Vehicles (EV) may introduce disturbances to the operation of the Power Gri... more The advent of Electric Vehicles (EV) may introduce disturbances to the operation of the Power Grid, due to the great demands of electric power that is required during the simultaneous charging of large EV fleets. Towards this end, novel approaches for the management of the EV charging have been proposed in recent literature. Nevertheless, the implementation of a framework that allows flexibility in the definition of the decision-making objectives, along with user-defined criteria is still a challenge. Towards addressing this challenge, a framework for the smart charging of EVs is presented in this paper. The smart charging is facilitated by a two-layer Genetic Algorithm that operates in Charging Stations with various types of chargers that are connected to multiple charging points in a resource-sharing manner. The benefits of the proposed approach are the fast optimisation time, the inclusion of userdefined criteria, and the extraction of feasible solutions considering the availability of the chargers in the station. The communications between the EV and the Charging Station are facilitated by the Open Platform Communications-Unified Architecture (OPC-UA) standard. The proposed algorithm succeeds into finding competitive solutions even during charging scenarios with conflicting criteria.

The digitalization of industry is targeting at the integration of artificial intelligence (AI) in... more The digitalization of industry is targeting at the integration of artificial intelligence (AI) in manufacturing systems, for delivering intelligent machinery. Although AI seems a long-term target, similar enabling technologies such as artificial neural networks (ANNs) have been introduced. Despite that ANNs are inspired by the human brain's functioning, understanding how they work and training them is a challenging task, requiring engineers with advanced math and coding skills. On the contrary, augmented reality (AR) is a cutting-edge digital technology, enabling the registration of 3D content on the physical environment, thus enhancing user's perception in a growing variety of scientific fields. Therefore, this research work aims at the design and development of an AR-based framework that facilitates the conceptualization of an ANN through AR, assists engineers train efficient ANN and moreover share knowledge through suitable communication channels. Finally, the framework can handle datasets with the use of cloud services.

The evolution of production systems encloses continuous adaptation of workplaces with changing le... more The evolution of production systems encloses continuous adaptation of workplaces with changing levels of technologies and automation. This research paper examines scenarios of multi-skilled operators, cooperating to accomplish a common goal. The under-consideration environment consists of a distributed network of workstations, each one assigned with a set of pending jobs. Therefore, the production engineer faces the challenging task of job allocation to suitable operators and appropriate workstations. As such, the formulation of the problem is based on the evaluation of each individual operator's job-related skills and the provision of an intelligent decision-making algorithm for the human resources allocation. The framework addresses the optimization of the allocated operators-jobs correlation and the workforce cost as the model's decision criteria. The model was implemented in a cross-platform planning application and tested in a real-life industrial scenario.

The shift of profit margins from products to services, has transformed traditional production equ... more The shift of profit margins from products to services, has transformed traditional production equipment supplier industries to providers of Industrial Product-Service Systems (IPSS). IPSS is a new business model for consistent delivery of industrial products such as production equipment and manufacturing services (Manufacturing as a Service). However, procurement of IPSS between industrial companies (i.e. Businessto-Business-B2B) is more complicated compared to the case of products offered to consumers (i.e. Business-to-Consumer-B2C). The complexity in interaction between the involved B2B stakeholders, the lack of trust and high costs especially for Small Medium Enterprises have hampered the establishment of standardized e-marketplaces in a similar manner as in the business to consumer world. This research work presents an overview on the requirements to support supply-chain processes on a digital B2B platform as well as a discussion of the objectives and the benefits of this multi-sided platform.