Improving lean design of production systems by visualization support

The design process of production systems is complex with many different aspects to consider for efficiently developing and installing an effective system. Important success factors during the design process are typically the abilities to identify and manage risks, develop mitigation plans, and conduct timely proactive problem solving. The work reported in this paper is part of research addressing methods for how the design process can be supported by using virtual representations of the factory environments captured with 3D laser scanning. This support is evaluated in an industrial study of one industrialization project in the manufacturing industry. The industrialization project follows the process to design layout, work places, and plan for installation of new equipment to create a production system within a refurbished shop floor area. The area will include CNC machining centers, welding stations, product inspection, product cleaning, and material handling. 3D laser scanning is used to provide an accurate and realistic virtual representation of the current shop floor area. This virtual representation is combined with 3D CAD models of the new machining centers and other equipment to provide a realistic visualization of the planned production system. The research approach and its questions investigate the benefits of combining the lean principles to design and development of production systems using a realistic visualization, which include systematic risk analysis and problem solving as important activities. The result shows that visualization support gave a great advantage to identify the possible risks and problems, which resulted in higher confidence and substantial timesaving in planning and execution of the industrialization project

Virtual factory layouts from 3D laser scanning – A novel framework to define solid model requirements

In a world with increasing customer demands, manufacturing companies must develop and produce products more rapidly and adapt their production systems offline, to not disturb the ongoing processes. This creates a demand of using digital production development so that development can be performed in parallel with production. Virtual factory layouts (VFLs) are essential for companies in order to plan their factory layout and evaluate production scenarios. However, requirements for a VFL depends heavily on its purpose. For example, the requirements on a model for offline programming of robots are different from those on a model used to determine buffer locations. There is currently a lack of clear guidelines for how developed a VFL should be to fulfil said requirements, which contributes to unnecessary modelling time and variation in delivery quality. This paper aims to put the actual demands and requirements of a VFL in focus. By adapting a Level of Development-framework for establishment of Building Information Models (BIMs) and connecting it to the purpose of VFLs, development of a framework for detail and functionality level of VFLs is enabled. Such a purpose-oriented framework will help to define delivery packages suited for different circumstances, which will provide the modeler with knowledge of how much detail and functionality a specific model should contain. The increased clarity provided by the developed framework results in a clearer connection between expected result and actual output from a custom VFL project. Also, by connecting model properties or development to the model-purpose, the framework brings clarity and structure to a currently vague field. This provides means for a more efficient and accurate use of VFLs, which will support the rapid development of production facilities

Synthesis of Manufacturing and Facility Data for Sustainability Analysis

This paper discusses data synthesis of production and facility knowledge for sustainability analysis by applying the ISA 95 "Activity Models of Manufacturing Operations Management" (MOM) model. Presently, production and facility management are "silo" operations, which basically function independently of each other. This paper presents the addition of facility activities to the MOM model, in accordance with the needs for attaining a holistic view of sustainability analysis. Historically, production and facility data are represented in various forms, e.g., data bases, CAD, and spreadsheets, without a common unifying representation. This paper addresses the issue by introduced Core Manufacturing Simulation Data (CMSD) Standard. A case study of the data synthesis for a precision sand casting production facility is provided

A tool for holistic assessment of digitalization capabilities in manufacturing SMEs

In a constantly evolving global market, manufacturing companies need to be flexible and adaptive to survive. Digital twins of production systems have been proposed as one part of the solution, however this comes with multiple challenges. Manufacturing SMEs have limited resources and need to direct their efforts in this area wisely. This paper presents a tool for holistic assessment of an SME manufacturer\u27s level of digitalization, in order to visualize current gaps and guide digitalization efforts over a production system\u27s life cycle. The tool was empirically developed together with Manufacturing SMEs and has strengthened their digitalization awareness and capabilities

Development of virtual reality support to factory layout planning

Virtual reality (VR) technology has become ever mature today with affordable and yet powerful hardware. In the manufacturing industry, there is a growing interest of adopting VR to improve existing work procedures. Factory layout planning (FLP) is a long standing area in production engineering that sees great potentials of VR integration. Virtual reality supported layout planning (VLP) is gaining wider attention in research and practice as the virtual environment allows designers to test out “what if” scenarios in relative ease. However, previous research of VLP mostly focus on general layout planning but not the detailed level planning. Also, it is reported that the virtual modeling process is time-consuming and costly. In this study, we propose a point cloud based virtual factory modelling approach for the VLP tasks. It incorporates point cloud representation of physical environment with CAD data to model the virtual factory with the aims of simplifying the modelling process and improving decision-making for the VLP tasks. The proposed approach is exemplified and refined through three industrial cases. The implementations and results of the cases are highlighted and discussed in details. At the end, a general guidance for VLP is extracted and presented for future point cloud based VR support in FLP tasks

Factory Radio Design of a 5G Network in Offline Mode

The manufacturing industry is connecting people and equipment with new digital technologies, enabling a more continuous stream of data to represent processes. With more things connected, the interest in a connectivity solution that can support communication with high reliability and availability will increase. The fifth generation of telecommunication, i.e., 5G has promising features to deliver this, but the factory environment introduces new challenges to ensure reliable radio coverage. This will require efficient ways to plan the Factory Radio Design prior to installation. 3D laser scanning is used at an ever-increasing rate for capturing the spatial geometry in a virtual representation to perform layout planning of factories. This paper presents how to combine 3D laser scanning and physical optics (PO) for planning the Factory Radio Design of a cellular Long-Term Evolution (LTE) network (5G) in a virtual environment. 3D laser scanning is applied to obtain the spatial data of the factory and the virtual representation serves as the environment where PO computation techniques can be performed. The simulation result is validated in this paper by comparison to measurements of the installed network and empirical propagation models. The results of the study show promising opportunities to simulate the radio coverage in a virtual representation of a factory environment

Integration of 3D Laser Scanning Into Traditional DES Project Methodology

Today’s product development cycles demand manufacturing system development to meet ever changing product requirements and shifting production volumes. To assess and plan production capacities, companies rely on decision support from simulation and modeling. The simulation models are used to test and verify scenarios in a non-disrupting environment. To efficiently model a manufacturing system physical familiarity with the real system is often necessary. Likewise, to communicate the results of a simulation model, its visual resemblance to the studied system provides input for decision makers. 3D laser scanning offers photorealistic 3D capture of spatial measurements and has successfully been used in manufacturing environments. This research proposes the integration of 3D laser scanning into a traditional simulation project methodology in order to aid decision-making. Some promising stages for integration have been identified based on a technology demonstrator in the aerospace industry

Integration of 3D Laser Scanning Into Traditional DES Project Methodology

Today’s product development cycles demand manufacturing system development to meet ever changing product requirements and shifting production volumes. To assess and plan production capacities, companies rely on decision support from simulation and modeling. The simulation models are used to test and verify scenarios in a non-disrupting environment. To efficiently model a manufacturing system physical familiarity with the real system is often necessary. Likewise, to communicate the results of a simulation model, its visual resemblance to the studied system provides input for decision makers. 3D laser scanning offers photorealistic 3D capture of spatial measurements and has successfully been used in manufacturing environments. This research proposes the integration of 3D laser scanning into a traditional simulation project methodology in order to aid decision-making. Some promising stages for integration have been identified based on a technology demonstrator in the aerospace industry

Integration of Life Cycle Inventories Incorporating Manufacturing Unit Processes

Sustainable manufacturing (SM) concerns the manufacture of products with regard to environmental, social, and economic impacts over the entire life cycle. With a primary focus on environmental concerns, life cycle assessment (LCA) can support SM practices. The life cycle inventory (LCI) is a key phase of LCA, and this paper considers the integration of manufacturing unit processes (MUPs) into system-level LCIs, which requires consideration of process flow diagrams at different levels of abstraction. Furthermore, uncertainty quantification is an important compo- nent of LCA interpretation, and this paper proposes a method to synthesize LCIs from the process-level to the system-level that consistently quantifies uncertainty in the inventories. The method can incorporate MUP data derived from measurements and/or modeling and simulation. Further development towards a complete methodology is discussed

Integration of Life Cycle Inventories Incorporating Manufacturing Unit Processes

Sustainable manufacturing (SM) concerns the manufacture of products with regard to environmental, social, and economic impacts over the entire life cycle. With a primary focus on environmental concerns, life cycle assessment (LCA) can support SM practices. The life cycle inventory (LCI) is a key phase of LCA, and this paper considers the integration of manufacturing unit processes (MUPs) into system-level LCIs, which requires consideration of process flow diagrams at different levels of abstraction. Furthermore, uncertainty quantification is an important compo- nent of LCA interpretation, and this paper proposes a method to synthesize LCIs from the process-level to the system-level that consistently quantifies uncertainty in the inventories. The method can incorporate MUP data derived from measurements and/or modeling and simulation. Further development towards a complete methodology is discussed