Shop Floor Control System Research Articles

The Sensor Network for Multi-agent System Approach in Smart Factory of Industry 4.0

This research was developed to plan, monitor, and control the production in a modern manufacturing system model with heterogeneous production facilities, consisting of several automatic machine tools and conventional machine tools. Therefore, it proposed, a smart factory concept that utilises computer technology, internet networks and sensors so that the production process can be monitored. The sensor network monitors the condition of the machine tools and the status of the job. The temperature sensors, the vibration sensors, the electrical energy sensors are used to check tool conditions in machine tools. Meanwhile, the radio frequency identification (RFiD) system is used to check the status of the workpiece whether it has been completed, work in progress, or is waiting in a buffer or a pallet stocker. The information relating to the performance of the machine tools is sent using the IoT application so that through the web. The machine performance data are collected, and their status can be monitored. Likewise, job status is visible on the shop-floor control system. The sensor network model at the prototype scale had been built and tested on a laboratory scale. The test results showed that the performance of machine tools and job status were monitored properly.

Using cloud computing technology to design and implementation of smart shop floor control system

Smart manufacturing has evolved and become more automated, computerized and cloud computing. The current shop floor control system (SFCS) has been implemented for many years, and has gradually encountered many problems. It moves towards the flexible smart manufacturing owing to the multiplex customer demand. Therefore, the current SFCS has been customized in many versions, which makes the low maintenance efficiency and the version control difficult. This paper is using cloud computing as a platform of developing and integrating multiplex customer demand to establish the integrity smart system function, and using Team Server to centralize the program versions to solve version management. Besides, the maintenance efficiency is raised by using production parameter configuration of the service-oriented design. The cloud based method enables deploying to be performed in any place other than the production line, which also facilitates the promotion of maintenance efficiency. The subscription function offered by the reporting service provides reports at specific time. The result of this research is to develop the cloud-based smart SFCS, which can achieve the goal of integrating production process and the promotion of production efficiency. With the system report, cloud-based smart SFCS can support managers to make right decision to promote the product quality.

Integration of machine operators with shop floor control system for Industry 4.0

Integration of machine operators with shop floor control system for Industry 4.0

Real-time scheduling for a smart factory using a reinforcement learning approach

Abstract Previous studies of the real-time scheduling (RTS) problem domain indicate that using a multiple dispatching rules (MDRs) strategy for the various zones in the system can enhance the production performance to a greater extent than using a single dispatching rule (SDR) over a given scheduling interval for all the machines in the shop floor control system. This approach is feasible but the drawback of the previously proposed MDRs method is its inability to respond to changes in the shop floor environment. The RTS knowledge base (KB) is not static, so it would be useful to establish a procedure that maintains the KB incrementally if important changes occur in the manufacturing system. To address this issue, we propose reinforcement learning (RL)-based RTS using the MDRs mechanism by incorporating two main mechanisms: (1) an off-line learning module and (2) a Q-learning-based RL module. According to various performance criteria over a long period, the proposed approach performs better than the previously proposed MDRs method, the machine learning-based RTS using the SDR approach, and heuristic individual dispatching rules.

Sociotechnical Evaluation of Alternative and Innovative Shop Floor Control Systems

In this paper we present a sociotechnical evaluation of three new, and alternative shop floor control systems used in high-variety/low-volume part manufacturing. The three alternative systems concerns the application of (i) POLCA, a card-based system to connect semi-autonomous cells, (ii) LPC (Lean Production Control), a detailed scheduling system to guide the flow of work in a low-volume/high-variety system, and (iii) the CONWIP/FISFOS/TAKT system, a system which limits the amount of work at the workfloor and only indicates priorities on job order level. We show how sociotechnical principles can be used to assess alternative shop floor control concepts. Concurrently, we discuss workplace innovation by means of the alternative shop floor control systems.

An Agent Based Distributed Shop Floor Control System for a Job Shop Environment

Abstract In addition to the inherent dynamism associated with any shop floor, a job shop environment exhibits certain additional features that promotes the use of decentralized over centralized decision support systems on the benchmark of responsiveness. The current work first highlighted the system level and operational complexities associated with a job shop environment and very objectively established the need for a decentralized decision support system for such set ups. Unlike various attempts of developing agent systems for shop floor, where major focus has been on imparting intelligence to scheduling agents, the current work took into account the need for integrating multiple shop floor functions, namely scheduling and maintenance, and demonstrated the development of a decision mechanism considering more than one shop floor function. The detailed design constitutes a global scheduling agent for entire floor and a set of local scheduling and maintenance agents for each machine on the floor. The novelty of the work lies in the thoroughness with which individual agent design has been attempted. The work reported in this paper added to the multiagent literature, specifically in the context of manufacturing, by answering certain questions like “how should intelligence be built into a shop floor agent?’ and ‘how could agents from different domains be integrated?” The work also highlights the fact that the advantage of agent features can be leveraged in true sense and systems based on them could be successful only if means of integrating heterogeneous functions are taken into account.

Automatic translation of plant data into management performance metrics: a case for real-time and predictive production control

A scalable and repeatable solution for linking shop-floor control system to a discrete event simulation (DES) model is presented. The key objective is to automatically translate the real-time data from the control system (e.g. supervisory control and data acquisition, SCADA) into KPI transfer functions of the production process. Such a seamless translation allows for the integration of engineering data emitted at plant level to higher level information system for decision-making. The solution provides a platform for researchers and practitioners to utilise the capabilities of real-time DAQ and control with that of discrete event simulation to accurately measure the key manufacturing systems performance metrics. In addition to the real-time capabilities, the predictive capabilities of the solution provide the managers to look ahead and to conduct What-if scenarios. Such capability enables line management to optimise performance and predict destabilising factors in the system ahead of time. A fully operational version of the designed solution has been deployed in a brewery’s live production system for the first time. The brewhouse production line model measures the utilisation of resources, Overall Equipment Effectiveness, and Overall Line Effectiveness in real-time and fast-forward mode simulation. The results of the predictive models (What-if-Scenarios) have been validated and verified by statistical means and direct observations. The accuracy of the estimated parameters is highly satisfactory.

Distributed, Autonomous Control in Production of Jet Turbine Parts

An industrial prototype of a distributed, autonomous shop floor control system (HolMS) has been developed based on the PROSA reference architecture for holonic manufacturing systems. The HolMS system challenges the concept of visual control as prescribed by the Kanban mechanism in the Toyota Production System. Instead, it applies a market oriented service request/service offer bidding mechanism. A basic premise for obtaining this on the shop floor is that the different processing units are able to communicate. This has been accomplished by developing OPC UA wrappers for all the CNCs, robot cells and tracking devices involved. The HolMS prototype has been demonstrated at the jet turbine vane department of GKN Aerospace Norway.

The development of a RFID and agent-based lot management controller for PROMIS in a client/server structure for IC assembly firm

Many integrated circuit assembly firms today are struggling in a low-profit environment. To survive in the semiconductor industry, it requires assembly firms to do their best efforts in enhancing their competitive advantages. One effective way for an assembly firm to enhance its competitiveness is the introduction of advanced technologies into its shop floor control system (SFCS) to improve assembly yield and lower assembly costs. In this study, two advanced technologies, Radio Frequency Identification and agent-based approach, were used to initiate a lot management controller (LMC), which played as a thin client in a client/server architecture to cooperate with PROMIS, a SFCS being widely used in the semiconductor industry. In addition, an eight-stage software process, which is based on Unified Modeling Language, is proposed to facilitate the development of the LMC.

Information Technology Education in a Digital Factory Learning Environment

This paper presents the vision, construction, and implementation of an Integrated Manufacturing Technology (IMT) laboratory for higher education. The laboratory introduces integration of Information Technology (IT) in manufacturing processes and provides hands-on learning experience in an authentic, holistic, and automated production environment, not commonly found in academic teaching. The manufacturing process includes fully-automated, semi-automated, and manual stations and is supported by a heterogeneous IT infrastructure, including manufacturing databases, shop-floor control, data warehousing, business intelligence, and enterprise systems. The IMT laboratory is used to facilitate learning in a databases course and a business intelligence course, resulting in positive feedback from the students.

Gaia Analysis and Design of a Multi-agent-based Shop Floor Control System

To achieve competitiveness in the today’s manufacturing plants; many researchers suggest agent based manufacturing systems, with scheduling and control activities distributed on several entities called agents. To develop this kind of systems some promising agent-oriented software methodologies, as Gaia, have been proposed. They provide the concepts and procedures to define the main features of multi-agent systems. In this paper we show how we used the Gaia methodology to analyze and design a multi-agent-based shop floor control system that has been further implemented by JADE. We also show preliminary computational experiments that show as our approach has a good performance in flexible environments.Key Words: shop floor control, scheduling and control, multi-agent systems, software engineering, Gaia analysis and design.Análisis y Diseño Gaia de un sistema multiagente de control de plantaResumen: Para mejorar el desempeño de las actuales plantas de producción, muchas investigaciones sugieren la implementación de sistemas de fabricación basados en agentes, donde las actividades de programación y control de la producción están distribuidas sobre varias entidades denominadas agentes. Para desarrollar este tipo de sistemas, durante las dos últimas décadas se han propuesto varias metodologías que proporcionan los conceptos y procedimientos para definir las principales características de los sistemas multiagente. En este ar tículo se muestra el proceso de análisis y diseño de un sistema multiagente de control de planta mediante Gaia, una de las metodologías de desarrollo de sistemas multiagente más aceptadas en la actualidad. El sistema ha sido posteriormente implementado mediante JADE. También mostramos algunos resultados experimentales que muestran que el desempeño de nuestra propuesta en entonos flexibles es satisfactorio.Palabras clave: control de planta, programación y control de la producción, sistemas multiagente, ingeniería de software, análisis y diseño Gaia.

A Novel Coordination and Control Approach for Manufacturing System

In order to handle dynamic and complex manufacturing environment, a novel coordination and control approachis proposed and applied to manufacturing control system in this paper. Using an implicit coordination approach, a novel coordination approach ,which is inspired by the hormone regulatory principle, can find efficient routing paths among the manufacturing resources automatically. With using the proposed implicit coordination approach, the manufacturing control system could reduce the amount of the control communication, and raise the sensitivity of the controller in the shop floor control system. Finally, a simulation experiment, using the proposed approach, is test. And the result confirms that the novel implicit coordination approach has excellent control performance in a static environment and good adaptability to disturbances in shop floor.

Decision support tool using concurrent engineering framework for agile manufacturing

Competitive situations have led to increasing attention being paid to customer satisfaction, of which timely and customised services are the key concepts. The need for a method of rapidly and cost-effectively developing products including design, process planning and shop floor control system has led to the concept of agile manufacturing. This paper proposes concurrent engineering (CE) framework using effective application of information technology and knowledge-based engineering using object oriented technology which will help adoption and implementation of agile manufacturing practices. This gives manufacturing units an extra edge in today’s cost and time competitive market. Considerable improvement was achieved in a machine tool manufacturing company on the basis of the methodology presented in this paper. CE was implemented for its new products, systems and processes are aligned and leads to agility to manufacturing. Lead time could decrease more than 50% compared with similar development projects carried out in this company.

Availability of material streams in hybrid push/pull shop floor control system

The paper presents practical aspects and example of integration of hybrid system controlling production system inputs including raw materials and components based on analytical and managerial expert system. The research is based on demand analysis of a large industrial company providing a wide range of assortment of about 150 final products manufactured according to made-to-order and make-to-stock strategy. The goal of the research was increasing availability of material in production system for multi-assortment production cells fed with hybrid pull/push strategy.

Research and Design on Workshop Job Management System Based on Web Electronic Digital Signage

The workshop job management system for improving manufacturing productivity and workshop information management plays an important role, while the electronic digital signage is seen as the core of shop floor control system. In this paper, the traditional electronic signage is proposed based on a new electronic digital signage network design, and its integration into the shop floor management systems. This paper developed job shop management system based on web electronic digital signage, the effective integration of existing hardware and software resources of the workshop, rational allocation of production resources of the workshop, the workshop production operations management to achieve digital control, reducing the workshop production costs, improve business efficiency. This paper presents the design of specific methods, and the establishment of a specific management model.

Using Theory of Constraints to Control Manufacturing Systems: A Conceptual Model

Since the Goldratt and Cox’s (1984) seminal study, Theory of Constrains has evolved from a simple production scheduling software into a management philosophy, with practices and principles spanning a multitude of operation management disciplines. A variety of studies has investigated how production control is carried out in a Theory of Constrains environment, but most of research available lacks in providing an overall vision of this issue. In order to contribute to this gap, using theoretical investigation and the empirical study of five case studies, this article compares the characteristics of TOC with those typical of three shop floor control systems, i.e. MRP, JIT and Daily Rate. As result, the research identifies an interpretative framework based on the distinguishing characteristics of Theory of Constrains. The framework supports the analysis of the nature and scope of these four systems by highlighting the main differences between them.

Dynamic Scheduling Using Immune Genetic Algorithm for Agile MES

As a bridge links the upper enterprise planning system and the lower shop floor control system, enormous real-time information interact in shop floor, which poses great difficulty for scheduling of manufacturing execution system(MES). To meet the requirement of MES agility in the volatile information environment, dynamic scheduling becomes one of most widely used methods. In this paper, a modified immune genetic algorithm which incorporates artificial immune mechanism into genetic algorithm is presented to solve dynamic job shop scheduling problems. Owing to its good solving capability and computing speed, the algorithm could utilize real-time production information to generate predictive and reactive scheduling solutions. At last, the algorithm is applied in a MT10×10 job shop proved to be effective in obtaining better solutions than traditional genetic algorithm.

Study on shop floor control system in semiconductor fabrication by self-organizing map-based intelligent multi-controller

To confirm semiconductor wafer fabrication (FAB) operating characteristics, the scheduling decisions of shop floor control systems (SFCS) must develop a multiple scheduling rules (MSRs) approach in FABs. However, if a classical machine learning approach is used, an SFCS in FABs knowledge base (KB) can be developed by using the appropriate MSR strategy (this method is called an intelligent multi-controller in this study) as obtained from training examples. A classical machine learning approach main disadvantage is that the classes (scheduling decision variables) to which training examples are assigned must be pre-defined. This process becomes an intolerably time-consuming task. In addition, although the best decision rule can be determined for each scheduling decision variable, the combination of all the decision rules may not simultaneously satisfy the global objective function. To address these issues, this study proposes an intelligent multi-controller that incorporates three main mechanisms: (1) a simulation-based training example generation mechanism, (2) a data preprocessing mechanism, and (3) a self-organizing map (SOM)-based MSRs selection mechanism. These mechanisms can overcome the long training time problem of the classical machine learning approach in the training examples generation phase. Under various production performance criteria over a long period, the proposed intelligent multi-controller approach yields better system performance than fixed decision scheduling rules for each of the decision variables at the start of each production interval.

Agent Based Infrastructure with RFID Technology for Autonomous Shop Floor Control System

Automatic shop floor control system in distributed computing context is one of the most important links in Computer Integrated Manufacturing (or CIM) system. For most agent-based manufacturing control systems, a real-time product data available mechanism is not considered. In this paper, an integrated approach of RFID technology and multi-agent system of shot-floor control is presented. The proposed framework uses RFID for tracking products in the system and also for attaching product manufacturing information. This shift from off-line planning systems to on-line control systems will facilitate implementations of real-time scheduling requirement in autonomous manufacturing environment.

Optimization for manufacturing system based on Pheromone

A new optimization approach, called pheromone, which comes from the collective behavior of ant colonies for food foraging is proposed to optimize task allocation. These ants spread pheromone information and make global information available locally; thus, an ant agent only needs to observe its local environment in order to account for nonlocal concerns in its decisions. This approach has the capacity for task allocation model to automatically find efficient routing paths for processing orders and to reduce communication overhead, which exists in contract net protocol, in shop floor control system. An example confirms that a pheromone-based optimization approach has an excellent allocation performance in shop floor.