Windo Hutabarat

Modelling collaboration using complex networks

Collaboration means working together to achieve a common goal or to solve a problem, and in modern businesses, it is an important factor for information sharing and quality. This is due to the ability of collaborations to shape the structure and behaviour of organisations through the pooling of expertise and standardising of work patterns. Grounded on complex network theory and collaborative design research, a mathematical model of information flow for analysing collaboration in organisations is proposed in this article. The model defines concepts for characterising organisational structures for collaboration and proposes indicators for assessing organisational behaviour in terms of collaboration within organisations. The article concludes by discussing the applications and limitations of the proposed model.

Discrete Event Simulation and Virtual Reality Use in Industry: New Opportunities and Future Trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets.

Information channel diagrams: an approach for modelling information flows

In this article, the ‘information channel diagram’ (ICD) approach is introduced as a diagrammatical tool for modelling information flow during the delivery phase of organisations in which goods are deployed or delivered to customers. An initial review and evaluation of current tools for modelling information flow will be conducted based on the characteristics of information flow during the delivery phases in organisations. Diagrammatic primitives and a prescribed modelling methodology for developing an ICD will be presented, and a case scenario of the delivery phase of an organisation within the health care sector will be applied to demonstrate the use of the ICD. The article concludes by discussing some applications, generalisation potential and limitations of the ICD approach.

Immersive Mixed Reality for Manufacturing Training

In the complex manufacturing sector a considerable amount of resources is focused on training workers and developing new skills. Increasing the effectiveness of those processes and reducing the investment required is an outstanding issue. In this paper, we present an experiment (n=20) that shows how modern metaphors such as collaborative Mixed Reality can be used to transmit procedural knowledge and could eventually replace other forms of face-to-face training. We implemented a Mixed Reality setup with see-through cameras attached to a Head Mounted Display. The setup allowed for real-time collaborative interactions and could simulate conventional forms of training. We tested the system implementing a manufacturing procedure of an aircraft maintenance door. The obtained results indicate that performance levels in the Immersive Mixed Reality training were not significantly different than in the conventional face-to-face training condition. These results and their implications for future training and the use of Virtual Reality, Mixed Reality and Augmented Reality paradigms in this context are discussed in this paper.

Monitoring and Digitising Human-Workpiece Interactions during a Manual Manufacturing Assembly Operation Using KinectTM

Automation boosts competitiveness of manufacturing companies and is pervasive in modern industry. However, skilled manual labour is still used in a variety of complex tasks and is currently irreplaceable. A solution may lie in understanding the interactions between a human worker and the workpiece during a manufacturing task and digitising these interactions to potentially enable automation of the task. In this paper, a method to observe, record and digitise human-workpiece interactions using the Microsoft KinectTM is described. A manual threaded-fit assembly of a two-component pen housing is chosen. Essential information about the manual assembly is extracted from the recorded interaction data. The developed mechanism being markerless and unobtrusive is helpful in recording human-workpiece interactions in a factory without affecting normal operations.

A product-service system approach to telehealth application design

A considerable proportion of current point-of-care devices do not offer a wide enough set of capabilities if they are to function in any telehealth system. There is a need for intermediate devices that lie between healthcare devices and service networks. The development of an application is suggested that allows for a smartphone to take the role of an intermediate device. This research seeks to identify the telehealth service requirements for long-term condition management using a product-service system approach. The use of product-service system has proven to be a suitable methodology for the design and development of telehealth smartphone applications.

Development of a tuneable test problem generator for assembly sequence planning and assembly line balancing

Assembly optimisation activities that involve assembly sequence planning and assembly line balancing have been extensively studied because of the importance of optimal assembly efficiency to manufacturing competitiveness. Numerous research works in assembly sequence planning and assembly line balancing mainly focus on developing algorithms to solve problems and to optimise assembly sequence planning and assembly line balancing. However, there is a scarcity in works that focus on developing problems to test these algorithms. In optimisation algorithm development, testing algorithms by a broad range of test problems is crucial to identify their strengths and weaknesses. This article proposes a generator of assembly sequence planning and assembly line balancing test problems with tuneable complexity levels. Experiments confirm that the selected combination of input attributes does control the generated assembly sequence planning and assembly line balancing problem complexity, and also that the generated problems can be used to identify the suitability of a given algorithm to problem types.

Combining virtual reality enabled simulation with 3D scanning technologies towards smart manufacturing

Recent introduction of low-cost 3D sensing and affordable immersive virtual reality have lowered the barriers for creating and maintaining 3D virtual worlds. In this paper, we propose a way to combine these technologies with discrete-event simulation to improve the use of simulation in decision making in manufacturing. This work will describe how feedback is possible from real world systems directly into a simulation model to guide smart behaviors. Technologies included in the research include feedback from RGBD images of shop floor motion and human interaction within full immersive virtual reality that includes the latest headset technologies.

Gesture Detection Towards Real-Time Ergonomic Analysis for Intelligent Automation Assistance

Manual handling involves transporting of load by hand through lifting or lowering and operators on the manufacturing shop floor are daily faced with constant lifting and lowering operations which leads to Work-Related Musculoskeletal Disorders. The trend in data collection on the Shop floor for ergonomic evaluation during manual handling activities has revealed a gap in gesture detection as gesture triggered data collection could facilitate more accurate ergonomic data capture and analysis. This paper presents an application developed to detect gestures towards triggering real-time human motion data capture on the shop floor for ergonomic evaluations and risk assessment using the Microsoft Kinect. The machine learning technology known as the discrete indicator—precisely the AdaBoost Trigger indicator was employed to train the gestures. Our results show that the Kinect can be trained to detect gestures towards real-time ergonomic analysis and possibly offering intelligent automation assistance during human posture detrimental tasks.

Multi-objective discrete particle swarm optimisation algorithm for integrated assembly sequence planning and assembly line balancing

In assembly optimisation, assembly sequence planning and assembly line balancing have been extensively studied because both activities are directly linked with assembly efficiency that influences the final assembly costs. Both activities are categorised as NP-hard and usually performed separately. Assembly sequence planning and assembly line balancing optimisation presents a good opportunity to be integrated, considering the benefits such as larger search space that leads to better solution quality, reduces error rate in planning and speeds up time-to-market for a product. In order to optimise an integrated assembly sequence planning and assembly line balancing, this work proposes a multi-objective discrete particle swarm optimisation algorithm that used discrete procedures to update its position and velocity in finding Pareto optimal solution. A computational experiment with 51 test problems at different difficulty levels was used to test the multi-objective discrete particle swarm optimisation performance compared with the existing algorithms. A statistical test of the algorithm performance indicates that the proposed multi-objective discrete particle swarm optimisation algorithm presents significant improvement in terms of the quality of the solution set towards the Pareto optimal set.