Specific Manufacturing Task Research Articles

Virtual Reality Teleoperation System for Mobile Robot Manipulation

Over the past few years, the industry has experienced significant growth, leading to what is now known as Industry 4.0. This advancement has been characterized by the automation of robots. Industries have embraced mobile robots to enhance efficiency in specific manufacturing tasks, aiming for optimal results and reducing human errors. Moreover, robots can perform tasks in areas inaccessible to humans, such as hard-to-reach zones or hazardous environments. However, the challenge lies in the lack of knowledge about the operation and proper use of the robot. This work presents the development of a teleoperation system using HTC Vive Pro 2 virtual reality goggles. This allows individuals to immerse themselves in a fully virtual environment to become familiar with the operation and control of the KUKA youBot robot. The virtual reality experience is created in Unity, and through this, robot movements are executed, followed by a connection to ROS (Robot Operating System). To prevent potential damage to the real robot, a simulation is conducted in Gazebo, facilitating the understanding of the robot’s operation.

A blockchain-based interactive approach between digital twin-based manufacturing systems

Cloud manufacturing provides an interactive environment for collaboration between digital twin-based manufacturing systems. However, access to the enterprise cloud by a significant number of digital twin systems would lead to bandwidth competition and severe delays. Therefore, the data exchange process needs to be improved in a more reliable and effective way. To tackle this issue, a blockchain-based data interactive approach is proposed to form the peer-to-peer data exchange mechanism between digital twin-based manufacturing systems. First, the manufacturing edge pool is developed given specific manufacturing tasks. The blockchain enables the digital twin manufacturing systems to exchange data effectively and safely. Besides, the application of the blockchain reduces the dependencies of the digital twin systems on the enterprise cloud and improves the flexibility of the workshops. Finally, the effectiveness of this method is verified by a case study on the engine.

A Graph-based and Declarative Approach to a Secure Resource Management in Smart Factories

The article presents an applied research using the Design Science Research Methodology for securely managing resources of smart factories via a graph-based approach combined with a declarative query language. This query language can be used to find appropriate production facilities that are able to fulfill specific manufacturing tasks. This approach is aimed to solve the problem with the management effort for production facilities using enumeration for naming these facilities for the manufacturing tasks. Thus, the security is ensured by identifying the “current” valid identities (resources). Additionally, the usage of deputy relationships leads to alternative production facilities if resources have a breakdown or have to be serviced which has an effect on the availability.

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Many industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences.

A credit-based dynamical evaluation method for the smart configuration of manufacturing services under Industrial Internet of Things

Most scheduling problems are required to follow rigid metrics, such as the maximum completion time, earliest deadline first, etc., ignoring the flexibility of manufacturing services (MSs) and the effects of their historical data hidden in millions of manufacturing activities. The historical data serves as a powerful basis for describing the comprehensiveness or credibility of the MS itself with the help of Industrial IoT enabling all equipment to communicate and take preventive actions. Similar to the bank credit for individuals, MSs should also have their own referential credit values when choosing the most suitable service for a specific manufacturing task. This paper summarizes the MS attributes from six aspects with sufficient sub-attributes. The fuzzy Analytic Network Process combined with the Cross-Entropy method is employed to evaluate the credit of MSs in the complex manufacturing network system. Such service scoring mechanism (SSM) can personify a comprehensive credit evaluation of services, where, a smart service configuration mode based on credit is proposed for carrying out the supply–demand matching with the help of the data-security technology. Subsequently, a credit-based manufacturing mode is derived under SSM. Numerical examples are carried out to demonstrate the validity of the matching mode. The result may assist manufacturers to allocate their manufacturing tasks in real time in a “credit” way and make quicker decisions in exceptional circumstances, while making the chosen service truly competent enough to finish the work, so as to further improve the customer satisfaction.

Diverse task scheduling for individualized requirements in cloud manufacturing

ABSTRACTCloud manufacturing (CMfg) has emerged as a new manufacturing paradigm that provides ubiquitous, on-demand manufacturing services to customers through network and CMfg platforms. In CMfg system, task scheduling as an important means of finding suitable services for specific manufacturing tasks plays a key role in enhancing the system performance. Customers’ requirements in CMfg are highly individualized, which leads to diverse manufacturing tasks in terms of execution flows and users’ preferences. We focus on diverse manufacturing tasks and aim to address their scheduling issue in CMfg. First of all, a mathematical model of task scheduling is built based on analysis of the scheduling process in CMfg. To solve this scheduling problem, we propose a scheduling method aiming for diverse tasks, which enables each service demander to obtain desired manufacturing services. The candidate service sets are generated according to subtask directed graphs. An improved genetic algorithm is applied to searching for optimal task scheduling solutions. The effectiveness of the scheduling method proposed is verified by a case study with individualized customers’ requirements. The results indicate that the proposed task scheduling method is able to achieve better performance than some usual algorithms such as simulated annealing and pattern search.

Cloud-based Job Dispatching Using Multi-criteria Decision Making

The dynamic nature of modern workshops and the change in availability of manufacturing equipment affects the allocation of manufacturing jobs. In order to cope with these requirements a module that ranks manufacturing equipment and proposes the best fitted machine to perform a specific manufacturing task according to capabilities, availability and suitability is needed. This paper presents such a framework for allocating tasks to manufacturing equipment according to the capabilities, the availability and the running cost of the manufacturing equipment. The decisions are made by using a multi-criteria decision making tool running in a Cloud environment with data being fed through web based protocols. The novelty of the proposed system lies in the fact that the solution is based on a Cloud Manufacturing environment and the selection process is based on the latest information regarding the machine tool data, received through a web interface. The functionality of the module is illustrated through a case study.

A Cloud Manufacturing Resource Allocation Model Based on Ant Colony Optimization Algorithm

Resources should be allocated efficiently in a cloud manufacturing environment, given specific cloud manufacturing task. We study on the optimal resource allocation after the qualitative analysis of the match between the tasks and the resources in this work. Along this line, many factors should be significant, including time, cost and quality of services. Moreover, the workload of equipments should also be considered, in order to achieve load balance and improve the efficiency of manufacturing and the productivity. Therefore, in this paper, based on a four-dimensional objective function, that is, time, cost, quality of services and the load balance, we adapt the Ant Colony Optimization (ACO) algorithm to find the optimal solution. We also present a case study to evaluate our model.

Discrete-event simulation for evaluating virtual organizations

Outsourcing is a major driver in the growth of virtual organizations (VOs) in the manufacturing domain. These outsourcing networks can be classified as VOs as they are created from different organizational entities for a specific purpose and exist for a specified period of time. This paper proposes the use of discrete event simulation (DES) as a means of evaluating proposed VO configurations within the request for quotation (RFQ) process. The work presented is targeted at manufacturing-based VOs that are created to carry out specific manufacturing tasks as outlined in an RFQ, rather than more general project-based VOs that are formed to carry out work within a less defined structure. Data from an existing virtual breeding environment (VBE), obtained during field research into outsourcing networks, is used to illustrate the use of DES to support VO creation. As DES requires a high level of skill to use, the design of an easy-to-use web-based application with an embedded simulation engine is described.

Generating a task-driven extended enterprise for e-manufacturing

Currently, e-manufacturing is considered as a new advanced philosophy in manufacturing areas. In order to win the competition in the 21st century global market extended enterprise presented based on e-manufacturing strategy is playing an important role in manufacturing enterprises. As such, this paper mainly concerns on the generation of extended enterprise and the key points include four parts. First point, it introduces the basic concepts of the e-manufacturing and extended enterprise. Second, it presents and develops three kinds of task-allocating strategies and models that are connected with direct assignment, acquaintance and stranger to implement the generation of extended enterprise concerning the specific manufacturing tasks where Analytic Hierarchy Process (AHP) is adopted as an algorithm to carry out the optimal evaluation and decision. Third, it adopts Java web solutions and mobile agent technologies to realise the above-mentioned task-allocating models and prototype. And finally, it presents a case study to demonstrate above ideas.

Using Mobile Agents to Schedule a Manufacturing Chain on the Internet

This paper is mainly concerned with putting forward a novel manufacturing chain model and a new scheduling model for manufacturing chains in networked manufacturing systems. The manufacturing chain model is formed by adopting extensive activity-network-diagram workflow technique. The scheduling model is built upon mobile agent technologies, e.g. aglets. It includes two different scheduling levels. One is defined as the process scheduling which implements the scheduling logic for distributive manufacturing sites or manufacturing cells based on a specific manufacturing task. The other is the node scheduling which realizes the scheduling logic for manufacturing equipments based on specific working procedures or working paces. High-level scheduling aglet templates are created to support the operations at the levels of manufacturing sites or manufacturing cells. To complement, low-level scheduling aglet templates are created to support the operations such as working procedures or working paces over manufacturing equipments. As a result, the model is able to deal with dynamic manufacturing chains and their scheduling.

Rapid response manufacturing through a rapidly reconfigurable robotic workcell

This article describes the development of a component-based technology robot workcell that can be rapidly configured to perform a specific manufacturing task. The workcell is conceived with standard and inter-operable components including actuator modules, rigid link connectors and tools that can be assembled into robots with arbitrary geometry and degrees of freedom. The reconfigurable “plug-and-play” robot kinematic and dynamic modeling algorithms are developed. These algorithms are the basis for the control and simulation of reconfigurable robots. The concept of robot configuration optimization is introduced for the effective use of the rapidly reconfigurable robots. Control and communications of the workcell components are facilitated by a workcell-wide TCP/IP network and device-level CAN-bus networks. An object-oriented simulation and visualization software for the reconfigurable robot is developed based on Windows NT. Prototypes of the robot workcells configured to perform the light-machining task and the positioning task are constructed and demonstrated.

Manufacturing process selection in engineering design. Part 2: a methodology for creating task-based process selection procedures

Part 1 (A.M. Lovatt, H.R. Shercliff, J. Mater Des., 19 (1998) 205–215) of this paper identified a need for a methodology to help to create selection procedures for specific manufacturing tasks, where the material and processing operation have, to some extent, already been defined. This paper develops such a methodology, and its aims are twofold: firstly to guide the designer through defining the requirements of the design and identifying the attributes of the relevant subset of processes which must be considered; secondly to lead the designer through an evaluation of a design considering both technical viability (including the product quality during processing and in the finished part), and economic viability. A critical development in this work is the incorporation of process modelling into the selection procedure, as a tool for capturing the coupling of material and process characteristics which govern whether the processing and performance targets can be met.

An integration of knowledge acquisition techniques and EBL for real-world production planning

The paper presents an approach to the integration of knowledge acquisition (KA) techniques and explanation-based learning (EBL). Knowledge acquisition techniques are used to delineate a problem class hierarchy for different manufacturing tasks in mechanical engineering. This hierarchy is stepwise formalized into a terminological representation language. The terminological descriptions are then combined with cases of specific manufacturing tasks and their solutions (in the form of production plans). Explanation-based learning is applied to the cases and skeletal plans are automatically constructed for the terminal classes of the problem class hierarchy. Such skeletal plans consist of a dependency structure with a sequence of operators, that can be instantiated to specific plans for all other problems of the class. An evaluation of the proposed KA/EBL integration demonstrates its strengths as well as certain limitations of explanation-based generalization.

Appropriate automation for flexible manufacturing

Flexible manufacturing systems (FMS) have met with great interest in research and practice in recent years. It is symptomatic of the present way of thinking of manufacturing planners that the term FMS already implies fully automated manufacturing. In actual practice, however, a less highly automated, but highly flexible, type of manufacturing is economically more reasonable in most cases, as is discussed in this paper. First, the striking alterations in manufacturing technology in a changing world are described. Next, alternative development approaches on the basis of a number of case studies, also in various countries, are reported. Finally, an attempt is made to indicate the methodology to be employed in order to arrive at a manufacturing process (more or less automated) optimally matched to a specific manufacturing task.

Appropriate Automation for Flexible Manufacturing

Abstract Flexible manufacturing systems(FMS) have met with great interest in research and practice in recent years. It is symptomatic of the present way of thinking of manufacturing planners that the term FMS already implies fully automated manufacturing while, in actual practice in most cases, a less highly automated, but highly flexible, type of manufacturing is much more reasonable economically as is discussed in this paper. First, the striking alterations in manufacturing technology in a changing world are described. Next, alternative development approaches on the basis of a number of case studies, also in various countries, are reported. Finally, an attempt is made to indicate the methodology to be employed in order to arrive at a manufacturing process (more or less automated) optimally matched to a specific manufacturing task. In view of the increasing use of computers in manufacturing, as characterized by the almost popular term of CLM (computer integrated manufacturing), automation first and foremost should be considered a multiple-choice, interdisciplinary design job. If this need for design were overlooked, CIM might well help to perpetuate anachronistic factory structures. Regarding automation (and technology in general)not as a constraint, but as a design problem, opens up the chance to see qualified live work and automated work not as irreconcilable contrasts, but as supplementary productive forces. Often this still requires rethinking at management level, where traditional human concepts and outdated structures are preserved, obviously for fear of losing control

Computer Vision Systems for Industrial Inspection and Assembly

Custom-designed computer vision systems are being applied to specific manufacturing tasks. Current development may lead to general-purpose systems for a broad range of industrial applications.