A Methodology for Continuous Quality Assurance of Production Data

High quality input data is a necessity for successful Discrete Event Simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a day-to-day engineering tool requires high quality production data to be constantly available. Unfortunately, there are no detailed guidelines that describes how to achieve this. Therefore, this paper presents such a methodology, based on three concurrent engineering projects within the automotive industry. The methodology explains the necessary roles, responsibilities, meetings, and documents to achieve a continuous quality assurance of production data. It also specifies an approach to input data management for DES using the Generic Data Management Tool (GDM-Tool). The expected effects are increased availability of high quality production data and reduced lead time of input data management, especially valuable in manufacturing companies having advanced automated data collection methods and using DES on a daily basis

An algorithm for data-driven shifting bottleneck detection

Manufacturing companies continuously capture shop floor information using sensors technologies, Manufacturing Execution Systems (MES), Enterprise Resource Planning systems. The volumes of data collected by these technologies are growing and the pace of that growth is accelerating. Manufacturing data is constantly changing but immediately relevant. Collecting and analysing them on a real-time basis can lead to increased productivity. Particularly, prioritising improvement activities such as cycle time improvement, setup time reduction and maintenance activities on bottleneck machines is an important part of the operations management process on the shop floor to improve productivity. The first step in that process is the identification of bottlenecks. This paper introduces a purely data-driven shifting bottleneck detection algorithm to identify the bottlenecks from the real-time data of the machines as captured by MES. The developed algorithm detects the current bottleneck at any given time, the average and the non-bottlenecks over a time interval. The algorithm has been tested over real-world MES data sets of two manufacturing companies, identifying the potentials and the prerequisites of the data-driven method. The main prerequisite of the proposed data-driven method is that all the states of the machine should be monitored by MES during the production run

Data quality problems in discrete event simulation of manufacturing operations

High-quality input data are a necessity for successful discrete event simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a daily manufacturing engineering tool requires high-quality production data to be constantly available. In fact, there has been a major shift in the application of DES in manufacturing from production system design to daily operations, accompanied by a stream of research on automation of input data management and interoperability between data sources and simulation models. Unfortunately, this research stream rests on the assumption that the collected data are already of high quality,and there is a lack of in-depth understanding of simulation data quality problems from a practitioners’ perspective.Therefore, a multiple-case study within the automotive industry was used to provide empirical descriptions of simulation data quality problems, data production processes, and relations between these processes and simulation data quality problems. These empirical descriptions are necessary to extend the present knowledge on data quality in DES in a practical real-world manufacturing context, which is a prerequisite for developing practical solutions for solving data quality problems such as limited accessibility, lack of data on minor stoppages, and data sources not being designed for simulation. Further, the empirical and theoretical knowledge gained throughout the study was used to propose a set of practical guidelines that can support manufacturing companies in improving data quality in DES

Consistency in Figure Posturing Results within and between Simulation Engineers

This paper presents the results of an effort to compare figure posturing results within and between simulation engineers. The simulation engineers simulated four manual tasks. Alternately they used a posture prediction tool, and alternately they were only allowed to apply manual adjustments of the body angles. The simulation engineers repeated each task six times and always with at least six days between each occasion, to minimize the subject’s rememberance of how the cases were carried out. Results show that the use of a posture prediction tool, in such complex tasks as the study includes, neither reduces needed time to fulfill a simulation, nor differences within or between simulation engineers. Differences in simulation results often originate from the different assumptions the simulation engineers have of the task when positioning the manikins. The differences could be minimized by a more careful order description and by such activities as simulation engineering days at assembly plants and by bringing the people working with human simulation tools together in the organization

Extending and demonstrating an engineering communication framework utilising the digital twin concept in a context of factory layouts

The factory layout is frequently planned in virtual environments, based on the experience of software tool users. This planning process is cumbersome and iterative to collect the necessary information, with a high risk of faulty inputs and updates. The digital twin concept has been introduced in order to speed up information sharing within a company; it relies on connectivity. However, the concept is often misunderstood as just a 3D model of a virtual object, not including connectivity. The aim of this paper is to present an extended virtual and physical engineering communication framework including four concepts: digital model, digital pre-runner, digital shadow, and digital twin. The four concepts are demonstrated and described in order to facilitate understanding how data exchange between virtual and physical objects can work in the future and having up-to date virtual environments enables simulating, analysing, and improving on more realistic and accurate datasets.CC BY 4.0This paper is a revised and expanded version of a paper entitled ‘Evaluating a digital twin concept for an automatic up-to-date factory layout setup’ presented at 10th Swedish Production Symposium (SPS2022), Skövde, Sweden, 26–29 April, 2022.The authors gratefully thank the support of Scania CV AB, the Research School Smart Industry Sweden, and the VF-KDO Project (Virtual Factories with Knowledge-Driven Optimization) funded by the Knowledge Foundation in Sweden; this support made the research possible.</p

The influence of virtual human model appearance on visual ergonomics posture evaluation.

The objective of this study was to investigate whether the appearance of virtual human models influences observers when judging a working posture. A task in which a manikin is manually assembling a car battery was used in the experiment. In total, 16 different pictures were presented to the subjects. All pictures had the same background, but included a unique posture and manikin appearance combination. 24 subjects consisting of manufacturing managers, simulation engineers and ergonomists were asked to rate and rank the pictures. The results showed that the virtual human model appearance influenced subjects when they rated pictures one by one: a more realistic manikin was rated higher than the identical posture visualized with a less natural appearance. This appearance effect was not seen when subjects ranked the pictures while looking at all of them at the same time. The study demonstrates that the human modelling tool used when showing and visually evaluating results makes a difference. To minimize subjective effects, a combination of visualizations and objective ergonomic assessment methods is recommended

Reduce of ergonomics design flaws through virtual methods.

A work method for product and production system development that includes virtual methods for ergonomics analysis is presented and argued.The proposed work method is described and illustrated with an example,which the authors believe shows how a virtual work method can contribute to a better workplace design, and thereby, if utilised, would have prevented some of the design flaws that existed in the actual final product design in the example. This paper will also present the outcome, gain, and setbacks that are connected to the use of virtual work analysis methods within a design process

Evaluating a Digital Twin Concept for an Automatic Up-to-Date Factory Layout Setup

Today, manufacturing factory layout setups are most often manually designed and kept up-to-date during their lifecycle with computer-aided design software’s, so that analyses, verification simulations, and decisions can continuously be done. This manual approach is a cumbersome iterative process to collect the necessary information, with a high risk of faulty inputs and updates. Often the virtual descriptions do not match the physical version of the factory setup. This research presents a digital twin solution where physical equipment is connected to a virtual representation of the same equipment and automatically updates the virtual environment with the spatial position of the physical equipment and a proposed way to evaluate it. The physical equipment either has inbuilt sensors or has been equipped with external wireless sensors to track the spatial position. The metadata are distributed via Node-RED (a tool to visualize Internet of Things) to the simulation software Industrial Path Solutions, where the virtual equipment is repositioned based on data from the physical equipment. The result shows that it is possible to send spatial position information from a physical equipment and update the corresponding virtual description of the equipment in its virtual environment. The accuracy of the updates has been evaluated with manual measurements. Hence, the virtual environment of the factory setup, i.e., the digital twin, updates automatically based on the data sent by the physical equipment. With an up-to-date virtual environment, more accurate simulations and optimizations of the factory setup can be achieved. Examples of such possibilities are to evaluate ergonomic conditions or to optimize robot paths for robot cells in realistic and up-to-date virtual environments. Also, one could imagine making virtual reality visits to hazardous or sensitive factory environments in a safe way or studying things that otherwise would be hard or impossible in the real world. CC BY-NC 4.0Andreas Lind [[email protected]]This research was realized with the support of Scania CV AB’s Global Industrial Development and the VF-KDO profile (Virtual Factories with Knowledge-Driven Optimization) at the University of Skövde, funded by the Knowledge Foundation. </p

Using Methods-Time Measurement to Connect Digital Humans and Motion Databases

To simulate human motions in DHM tools, using techniques which are based on real human data is one promising solution. We have presented a solution in this study to connect motion databases with DHM tools. We have showed that using a motion database with MTM-based annotations is a promising way in order to synthesize natural looking motions. A platform consists of a Motion Database, a Motion Generator, and a DHM tool was introduced and tested. The results showed successful application of the presented platform in the designed test case