Shop Floor Monitoring Research Articles

An Augmented Reality Framework for Visualization of Internet of Things Data for Process Supervision in Factory Shop-Floor

Modern industrial environments provide a high level of digitalization, enabling great volumes of information to be used for shopfloor monitoring and control purposes. In cases where human operators participate in the production process, it is important to support operator’s intervention with Internet of Things (IoT) data and empower process supervision with constant information over Key Performance Indicators (KPIs). Towards this end, the proposed framework exploits Augmented Reality (AR) for the provision of an IoT data visualization solution to support KPIs based process supervision in the smart factory environment. The solution utilizes IoT-enabled components, in order to receive dynamic information over the status of sensors and resources spread across the factory shop-floor. The AR application facilitates the need for visualization of information available on the network, on the actual shopfloor components, which offer transparency and ease the supervision of production processes. The development of the AR and cloud API has been based on CSharp and Java, in a reusable framework that can be reused for similar industrial cases. The reconfigurability and reuse of the AR solution is supported by a template configuration, allowing industry practitioners to configure application features and external connections without any additional software development. The solution was validated on a thermoforming process supervision case of a white goods production system. The main goal was to use the AR framework to support operators during the process parameters design phase, and dynamic supervision of the shopfloor environment. It is demonstrated that the proposed system can be used for KPIs monitoring of the production cycles and for empowering process supervision and optimization.

Big data, industry 4.0 and cyber-physical systems integration: A smart industry context

The advancements in the industries have paved the way for the distributed establishment of the big data volumes, cyber-physical systems, and industrie 4.0. The perspectives of modules are integrated with the shop-floor monitoring and controlled by computational paradigms, and digital computational spaces. The performance rises after introducing an intelligent and automated manufacturing industry into the next-generation industry. The scope of this paper is to address the state-of-the-art technologies and phases such as digital twins, big data analytics, artificial intelligence, and internet-of-things. The research challenges are examined with attention on data integrity, data quality, data privacy, data availability, data scalability, data transformation, legitimate and monitoring issues, and governance. Lastly, potential research issues that need considerable research efforts are summarized. We believe that this paper is presenting the research directions for researchers in the area of smart industry towards its integration for the advancements of the industrial sector, and agile management. Some surprising development as industry 4.0 integration with socio-technical systems was found in designing the architecture of vertical, horizontal, and end-to-end integration mechanisms.

A modular factory testbed for the rapid reconfiguration of manufacturing systems

The recent manufacturing trend toward mass customization and further personalization of products requires factories to be smarter than ever before in order to: (1) quickly respond to customer requirements, (2) resiliently retool machinery and adjust operational parameters for unforeseen system failures and product quality problems, and (3) retrofit old systems with upcoming new technologies. Furthermore, product lifecycles are becoming shorter due to unbounded and unpredictable customer requirements, thereby requiring reconfigurable and versatile manufacturing systems that underpin the basic building blocks of smart factories. This study introduces a modular factory testbed, emphasizing transformability and modularity under a distributed shop-floor control architecture. The main technologies and methods, being developed and verified through the testbed, are presented from the four aspects of rapid factory transformation: self-layout recognition, rapid workstation and robot reprogramming, inter-layer information sharing, and configurable software for shop-floor monitoring.

Investigation of the feasibility of using microphone arrays in monitoring machining conditions

Acoustic Signals (AS) have been investigated as a way to monitor machines. In this work, close attention was paid to the size as well as the accuracy of the data for using a 32-element spherical microphone array to monitor end milling operations. By completing experiments varying standard milling parameters, mathematical models showing the change in AS for end milling with a single carbide cutting edge were determined statistically. It was found that this method of shop floor monitoring is useful and could be the future of real-time monitoring when implemented based on the findings regarding accuracy and size of the collected data.

Cloud-Based Augmented Reality Remote Maintenance Through Shop-Floor Monitoring: A Product-Service System Approach

Maintenance and its cost continue, over the years, drawing the attention of production management, since the unplanned failures decrease the reliability of the system and the return of investments. Maintenance services of manufactured products are among the most common services in the industry; they account for more than half of the total costs and influence the environmental impact of the product. In order for manufacturers to increase their productivity, by performing accurate and quick maintenance, advanced monitoring systems should be considered in order to easily detect machine tool failures before they occur. Toward that end, a cloud-based platform for condition-based preventive maintenance, supported by a shop-floor monitoring service and an augmented reality (AR) application, is proposed as a product-service system (CARM2-PSS). The proposed AR maintenance service consists of algorithms of automated generation of assembly sequences, part movement scripts, and improved interface that aim to maximize existing knowledge usage while creating vivid AR service instructions. Moreover, the proposed monitoring system is supported by a wireless sensor network (WSN), and is deployed on a Cloud environment together with the AR tool. The monitoring system monitors the status of the machine tools, calculates their remaining operating time between failures (ROTBF), and identifies the available windows of the machine tools in order to perform the AR remote maintenance. In order to validate the proposed methodology and calculate its impact, it is applied in a real-life case study of a white-goods industry.

Research on the key technology of non-standard automation control system development platform with shop-floor management and monitoring functions

With the development of industrial automation technology, non-standard automation devices have attracted more and more attention in modern manufacturing enterprise for its flexibility and customisation features. To deal with increasing requirements of rapid and customised development of non-standard automation control systems, soft PLC model of CoDeSys, which complies with IEC 61131-3, and the protocol of industrial real-time Ethernet (RTE) Ethernet for manufacture automation control (EtherMAC) are analysed. Design method of industrial RTE EtherMAC component library which based on CoDeSys runtime system (RTS) component library is studied. Then CoDeSys OPC communication model and database for shop-floor data access are studied as well. Based on these works, a non-standard automation control system development platform is designed and implemented through the combination of CoDeSys and EtherMAC. This platform integrates industrial RTE EtherMAC component library and database to provide modules for developers to achieve not only logic and motion control functions but also shop-floor management and monitoring. In order to verify the flexibility and feasibility of the development platform, a solar panel automatic laying machine control system with shop-floor management and monitoring functions is designed through the platform.

A Cloud-based Approach for Maintenance of Machine Tools and Equipment Based on Shop-floor Monitoring

Maintenance and its cost continue, over the years, to draw the attention of production management since the unplanned failures decrease the reliability of the system and also the return of investments. Advanced maintenance techniques that capture and process shop-floor information can reduce costs and increase the sustainability of an enterprise. This paper presents a condition-based preventive maintenance approach integrated into a machine monitoring framework. The latter acquires data from shop-floor machine tools and analyses them through an information fusion technique to support the condition-based preventive maintenance operations. The proposed approach is developed into a software service, deployed on a Cloud environment. The service gathers and processes data, such as their actual processing time and machining time per tool, related to the operation of machine tools and equipment and calculates the expected remaining useful life of components. Moreover, it provides notifications to machine tool operators and maintenance departments, as well as it enables the communication among them using mobile technology. The framework is applied to a case study with data obtained from a machining SME.

Research on the key technology of non-standard automation control system development platform with shop-floor management and monitoring functions

Research on the key technology of non-standard automation control system development platform with shop-floor management and monitoring functions

Discrete-Event Shop-Floor Monitoring System in RFID-Enabled Manufacturing

In this paper, a real-time discrete-event (DE)-based monitoring system is developed for radio-frequency identification (RFID)-enabled shop-floor monitoring in manufacturing industries. The monitoring system uses rigorous mathematical techniques for event construction, state prediction, and disturbance detection that are suitable for big-data environments of modern complex manufacturing systems. The biggest challenge is to design an efficient scheme for computers to process the event data fast and for engineers to modify the monitoring rules conveniently. First, a DE observer is designed to construct complex events from the simple events extracted from the raw RFID data. The DE observer is based on matrices with binary entries, and thus is easy for multiple users to interpret and modify to define new events or delete event definitions. Temporal relations between time-related events are also included. Second, a hidden Markov model, which considers the impact of user actions and disturbance events, is developed to predict the belief state of manufacturing systems and detect disturbances. Finally, an application case study of the developed system in the shop-floor monitoring of a precision machining parts manufacturing process is provided to show how it can help engineers/managers monitor the events and states efficiently.

생산현장 모니터링을 이용한 중소 제조기업용 비가동 시간 수집 및 분석

생산현장 모니터링을 이용한 중소 제조기업용 비가동 시간 수집 및 분석

J3D-based monitoring and control for e-ShopFloor

The objective of our research is to develop a web-based collaborative framework called web-based integrated sensor-driven e-ShopFloor (Wise-ShopFloor). The framework is designed to use the popular client-server architecture and View-Control-Model (VCM) design pattern with secure session control. The proposed solutions for meeting both the user requirements demanding rich data sharing and the real-time constraints are: (1) using interactive scene graph-based Java 3D models instead of bandwidth-consuming camera images for shop floor visualisation; (2) transmitting only the sensor data and control commands between models and devices for monitoring and control; (3) providing clients with user-friendly GUI for shop floor navigation and (4) deploying control logics in an application server. This paper presents the basis of the framework for building web-based collaborative systems that can be used for web-based manufacturing. A proof-of-concept prototype system is developed on top of the framework to demonstrate one of its potential applications on shop floor monitoring and control.

Wise-ShopFloor: A Web-Based and Sensor-Driven e-Shop Floor*

Targeting the remote monitoring and control of shop floors, this paper proposes a new framework called Wise-ShopFloor (W¯ebbasedi¯ntegrateds¯ensor-drivene-ShopFloor¯) that can be applied to distributed manufacturing environments. It utilizes the latest Java technologies (Java 3D and Java Servlet) for system implementation. This Web-based framework allows users to monitor and control a distant shop floor device with visual helps enabled by Java 3D models instead of camera images. The behavior of a 3D model is driven by sensor signals of its physical counterpart. A prototype system is developed to demonstrate its application on shop floor monitoring and control.

Issues on the architecture of an integrated general-purpose ShopFloor control software system

The software necessary to carry out integrated control over individual shopfloor components has not been commercially available up to the present. Although some subjects of shopfloor control (SFC), such as production scheduling and shopfloor monitoring, have been extensively studied and matured solutions are now available. Rapid generation of SFC software for integrated control of shopfloors remains a challenge. In this paper, the design principles of an integrated software framework for SFC, for the purpose of facilitating integration and implementation of SFC for any specific shopfloor manufacturing system, is discussed. Keys to our integrated software framework are the use of open architecture; the creation of ontology for shopfloor and the normalisation of shopfloor control activities; and the application of agent concept and a hybrid control architecture.

Using the chi-square statistic to monitor compositional process data

Summary We investigate the use of the chi-square control chart as a simple multivariate method for shopfloor monitoring of compositional process data. Although this chart is usually considered to be applicable only with multinomial process data, we show that it is also valid, in a certain asymptotic sense, for compositional data that arise from the Dirichlet distribution. For general compositional data, we show that the chi-square statistic can be used for process monitoring, provided that we make a simple adjustment to the degrees of freedom in the chi-square reference distribution. This method is illustrated and compared in four examples with the T 2 chart based on log-ratio transformation of the data.

A Simulation-Based Shop Floor Monitoring and Decision Support System

A Simulation-Based Shop Floor Monitoring and Decision Support System

Mechanics of the die coating application in the permanent mould casting process

The present study is intended to provide a basis for the practical implementation of shop-floor monitoring and control of an operation which, in the production sequence, accounts most for the variability of the permanent mould casting process. After describing the purpose and nature of the coatings applied on permanent mould cavities, their expected functional properties were analysed. The physical parameters governing the spray process have been isolated and their relation to the thickness of the coating deposit derived. The covering capability of the spray process in the early stage of the operation has been studied. Experimental observations are presented for two commercial coatings of widely different properties and usage. Finally, spray gun handling has been shown to affect the uniformity of the coating thickness along with the aspect ratio of the spray cone.

A conceptual framework for shopfloor production activity control

Abstract It is now recognized that production activity control (PAC) is a key factor of productivity. Some aspects of this theme, such as scheduling of production operations or shopfloor monitoring, have been the subject of extensive research and solutions are now available and regularly used in industry. In spite of this, PAC remains a complex activity for which no generic solution is available. In this paper, we suggest a conceptual framework for PAC which aims to provide support for the choice and integration of the various components of a PAC system. Several types of PAC modules are suggested and have to be chosen and organized in relation to the workshop characteristics. This proposal is supported both by a bibliographic study of current approaches and by the requirements expressed in AEROSPATIALE'S shopfloors.

CIM and the Production Monitoring and Control Systems

In this article, the implementation process of Shop Floor Monitoring and integration of automation islands of CIM has been described. Different Networking systems have been analyzed and the selection criteria have been outlined. This network have been applied to several CNC machine tools in TOFAŞ to monitor the production process, the efficiency of the machines and also to communicate the part programme lists. With this system the details of the efficiencies related to the machine or the production process can be monitored automatically and can be viewed on a central computer. Besides, the details of the error messages and the related statistical analyses can be obtained to help for preventive maintenance and the Total Productive Maintenance Studies. Possibilities of extending the system to quality control applications and Statistical Proccss Control (SPC) are investigated.

New Approaches to Shop Floor Scheduling in the Engineering Industry

Shopfloor scheduling as part of production control has to realize and optimise the allocation of available production resources to best satisfy some set of objectives. Up till now this task has been carried out in central planning departments. A product oriented work organization gives the chance to integrate planning and operating tasks on shop floor. ESPRIT project 1217(1199) "Human Centred CIM Systems" has identified a production island work organization and developed skill based information technology tools for the shop floor. The Bremen contribution to the project, the shop floor monitoring and control system (SMC) IKARUS, will be presented in this paper.The use of this kind of system will enlarge and enrich the work contents of the qualified island team. The autonomy and self control of team work will be supported as well as transparency will be gained on central production planning level. If system design and work organization design follows human centred principles it seems to be possible to combine human aspects and CIM.

Examples of Human-centred Work Design in CIM Structures

An ESPRIT-project of international participation has designed human-centred CIM structures. A newly developed electronic CAD sketch-board is to link the tasks and activities of designers and machine workers. A novel type of graphically interactive CNC-control, capable of simulations is supposed to relieve programme input on the shop floor and to strengthen the competence and qualification of skilled labour. A perfected computer-aided shop floor monitoring and control system installed in a partly autonomous production island is intended to combine the planning, performance and control of work to one comprehensive activity again in a decentralized and self-controlled way. A configuration of these three information-technological components is being set up as a CIM demonstrating island, and will be tested under participation of user groups in simulated industrial situations. The exemplary solution of the organizational design of a partly autonomous production island claims to demonstrate that there need not arise a contradiction between an advanced computer technology for the integration of all of a company's departments and processes on the one hand, and human- centred structures on the other, but that human activities and qualifications may be of truely integrating significance in CIM structures.