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  • 1.
    Abeysekera, John
    et al.
    ndustrial Ergonomics, Work Science Academy (WSA), Linköping.
    Illankoon, Prasanna
    Work Science Academy (WSA), Kandana, Sri Lanka.
    The demands and benefits of ergonomics in Sri Lankan apparel industry2016In: Work: A journal of Prevention, Assesment and rehabilitation, ISSN 1051-9815, E-ISSN 1875-9270, Vol. 55, no 2, p. 255-261Article in journal (Refereed)
    Abstract [en]

    Apparel exports bring in sizeable foreign income to Sri Lanka. To protect and promote this industry is a paramount need. This can be carried out by applying Human Factors/Ergonomics (HFE) which has proved to control negative effects at work places. This paper reports a case study which describes the demands and benefits of HFE in MAS Holdings which owns a large share of the apparel industry in Sri Lanka.The study consisted of walk through observation survey, a questionnaire survey and ergonomic work place analysis followed by a training programme to selected employees in three companies.Positive responses to questionnaires revealed good ergonomic practices in the work places surveyed. Ergonomically unfit chairs and potential hazards e.g. exposure to noise and hot environment were detected. It is seen that MAS have introduced strategies originated by Toyota Production System viz. 5S, Kaizen, six sigma etc., which are in fact ergonomic methods. A progressive project MAS boast of viz. ‘MAS Operating System’ (MOS) empowers training and development to employees.MAS Holdings has adequately realized the benefits of applying HFE as evident by the number of awards received. Relevant companies were advised to take appropriate corrective measures to control the potential hazards.

  • 2.
    Illankoon, Prasanna
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Hierarchical Controls Assessment for Ergonomics Risks in Maintenance Operation: An applied research2015In: Third Ergonomics International conference: Applications of ergonomics in developing countries: reality and perspectives / [ed] Professor H. Boudrifa, 2015, p. 115-128Conference paper (Refereed)
    Abstract [en]

    Today, Sri Lanka stands strong as one of the premier fashion and apparel outsourcing hubs in the world, possessing a wealth of long established culture which represents ethical entrepreneurship and sustainability. At present, the country is on a seamless and relentless process of setting up a unique platform to accomplish its ascendancy through superior quality, incomparable turnaround time and adoption of state-of-the-art technology. www.ft.lk (2015). Plant maintenance plays a major role on efficiency of manufacturing process and to have apparel sectors’ recognition over safe plant operations, maintenance functions have to be well complying with safety standards. Maintenance operation involves unique Human Factor challenges due to both Physical demands under restricted access and Psychological demands such as problem solving.  Due to these challenges, maintenance operation is recognized as carrying risks on the system as well as on the human. Risk evaluation with hierarchy of controls is a methodology utilized in industry in the management of hazards and risks to eliminate or reduce employee exposures. Elimination, Substitution, Engineering Controls, Administrative Controls and Personal Protective Equipment (PPE) is the common hierarchy used when identifying solutions to minimize employee exposure to the hazards. BS 8800 (2004). This applied research is based on an Industrial Project where Risk Evaluation was conducted with focus in determining the ways of preventing from Ergonomic Risks in maintenance operation. Hierarchy of controls being the basis, this research presents the evaluation done over the maintenance operation, risk preventions methods and suggests a Study Model that might be used generally in industry to determine Ergonomic Risk Prevention of Maintenance work.

  • 3.
    Illankoon, Prasanna
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Soft Issues of Industry 4.0: A study on human-machine interactions2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Autonomous industrial operations are becoming the norm due to advancements in technology, which has led to both advantages and disadvantages for the organisations involved. The use of intelligent systems has resulted in higher system reliability, a higher quality product, and reduced risk for human error. These systems collect large amounts of information, analyse them, make predictions, and take decisions, of which humans cannot do in the same capacity, have led to new and expanded levels of interactions. One key aspect concerns the fact that human interaction has decreased although has become more critical than before. Even if the systems are advanced and automated, human intervention is still necessary: such as maintenance actions, selection of data to train the system, and advanced decision making. Human intervention is especially crucial when dealing with complex and safety critical systems, where and when immediate interventions are required. Moreover, an expert human can improvise and make novel decisions in a capacity that present intelligent systems cannot. The problem is that both humans and machines need assistance to perform well. Autonomous operation is not perfect and when problems arise, humans must react. Although it is common that humans when not actively interacting with the system tend to lose perspective and find it difficult to quickly analyse a situation when it arises. Which means that they “fall out of the loop”. Their ability to gain a good understanding of the situation and make good decisions when the system suddenly needs their interaction is lost. In other words, humans have lost their situation awareness (SA) and a good SA it is needed in dynamic environments if they are to intervene quickly and successfully. If, and when a system can assist a human to quickly assess the situation and get back “into the loop” then the human can make educated decisions in a much quicker fashion. The purpose of this research was to explore and describe the importance of SA in maintenance and to recommend how to develop and provide better SA for intelligent maintenance systems (IMS).

    This thesis consists of a literature study conducted to develop the theoretical framework and two case studies were used to test the theoretical concepts. The thesis work tested five systematic methodologies to find suitable interventions to fulfil the SA requirements. The first case study focused on SA requirements during maintenance execution in a manufacturing organisation; there a quick return to production was the focus. The second case study was SA requirements in maintenance in the aviation domain, where safety is a top priority. The case study data were collected using interviews, observations, focus groups, and archival records. These qualitative data were analysed using qualitative content analysis, cognitive task analysis, and case taxonomic analysis.

    This work resulted in the identification of seven key SA requirements for maintenance: consisting of detection of abnormalities; diagnosing and predicting their behaviour; making changes in system configuration; compliance with maintenance standards; conducting effective maintenance judgements; maintenance teams; and for safe maintenance work. Five strategies to maintain SA were identified: explicit knowledge status, sense making, recognition primed decision making, skilled intuition, and heuristics. We also argue why IMS will make it difficult for humans to use most of these strategies to maintain SA in future. Finally, a new theoretical model for decision support (Distributed Collaborative Awareness Model) was developed. The study also shows how to apply these interventions in the railway maintenance sector. In conclusion, this study shows that in the maintenance domain, keeping humans in the loop requires a novel collaborative approach where the integration of the strengths of intelligent systems and human cognition is necessary. We also argue that a better understanding of SA strategies will lead to the further development of SA support for the human operator and maintenance technician.

  • 4.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Abeysekera, John
    Work Science Academy, Sweden.
    Ergonomics Motives in Lock-Out and Tag-Out Implementation: An applied research2014In: Second International Conference on The Application of Ergonomics in developing countries: Ergonomics in the service of development / [ed] Professor Hamou Boudrifa, Algiria, 2014, Vol. May, p. 72-83Conference paper (Refereed)
  • 5.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Abeysekera, John
    Work Science Academy, Sweden.
    Singh, Sarbjeet
    Mechanical Engineering Department, Government College of Engineering & Technology, Jammu.
    Ergonomics for enhancing detection of machine abnormalities2016In: Work: A journal of Prevention, Assesment and rehabilitation, ISSN 1051-9815, E-ISSN 1875-9270, Vol. 55, no 2, p. 271-280Article in journal (Refereed)
    Abstract [en]

    BACKGROUND:

    Detecting abnormal machine conditions is of great importance in an autonomous maintenance environment. Ergonomic aspects can be invaluable when detection of machine abnormalities using human senses is examined.

    OBJECTIVES:

    This research outlines the ergonomic issues involved in detecting machine abnormalities and suggests how ergonomics would improve such detections.

    METHODS:

    Cognitive Task Analysis was performed in a plant in Sri Lanka where Total Productive Maintenance is being implemented to identify sensory types that would be used to detect machine abnormalities and relevant Ergonomic characteristics.

    RESULTS AND CONCLUSIONS:

    As the outcome of this research, a methodology comprising of an Ergonomic Gap Analysis Matrix for machine abnormality detection is presented.

  • 6.
    Illankoon, Prasanna
    et al.
    Avery Dennison RIS Lanka (Pvt) Ltd, Information and Brand Management Division University of Moratuwa, Department of Management of Technology Katuwana, Homagama.
    Manathunge, Yamuna
    National Institute of Technical Education of Sri Lanka Kandawala, Rathmalana,.
    Identifying the psychological effects of short, repetitive and easy tasks on production lines2008In: ICPQR 2008: Proceedings of the 13th International Conference on Productivity and Quality Research / [ed] Jaakko Kujala; Päivi Iskanius, Oulu, Finland: University of Oulu, 2008, p. 221-231Conference paper (Refereed)
    Abstract [en]

    The apparel industry is recognised for repetitive tasks that undergo in cycle times of 1 to 3 minutes. These repetitive tasks would make robots of workers leading to destruction of human values resulting in poor productivity. This study was conducted to identify the psychological effects on garment production lines. Fifty female workers of a medium size garment factory located in the North-Western province, Sri Lanka answered a structured questionnaire and each was interviewed for 15 minutes. The production records were analysed and the common pattern in variation of productivity throughout the day was identified. Results show that the workers in apparel production lines experience combined effects of boredom and stress. This is evident by the mismatch between the pattern obtained for variation of productivity and the “U“ shape which had been proposed by earlier researchers considering the effects of boredom alone. This fact was further verified as 56% of the workers who responded to the questionnaire declaring that the stress, which drives them towards hourly targets, helps alleviate boredom. The findings would be important for further research on application of possible methods to decrease boredom and stress such as by job rotation, recommending appropriate rest pauses, applying music and paying bonus for productivity.

  • 7.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Manathunge, Yamuna
    Department of Education and Training, University of Vocational Technology, Ratmalana, Sri Lanka.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Abeysekara, John
    Work Science Academy, Kandana, Sri Lanka.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lockout and Tagout in a Manufacturing Setting from a Situation Awareness Perspective2019In: Safety, ISSN 2313-576X, Vol. 5, no 2Article in journal (Refereed)
    Abstract [en]

    Applying lockouts during maintenance is intended to avoid accidental energy release, whereas tagging them out keeps employees aware of what is going on with the machine. In spite of regulations, serious accidents continue to occur due to lapses during lockout and tagout (LOTO) applications. Few studies have examined LOTO effectiveness from a user perspective. This article studies LOTO processes at a manufacturing organization from a situation awareness (SA) perspective. Technicians and machine operators were interviewed, a focus group discussion was conducted, and operators were observed. Qualitative content analysis revealed perceptual, comprehension and projection challenges associated with different phases of LOTO applications. The findings can help lockout/tagout device manufacturers and organizations that apply LOTO to achieve maximum protection.

  • 8.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Distributed, Collaborative Awareness Model for Maintenance Decision Support.2020In: IEEE Access, E-ISSN 2169-3536Article in journal (Refereed)
    Abstract [en]

    Maintenance decision errors can result in very costly problems. With the rise of 4th industrial revolution, Intelligent Decision Support Systems are growing quickly. However, a key concern has been to better understand the linkage between the technicians’ knowledge and Intelligent Decision Support Systems. The research reported in this study has two primary objectives. (1) to propose a theoretical model that links technicians’ knowledge and intelligent decision support systems, and (2) to present a use case how to apply the theoretical model. As the foundation of the new model, is the assentation of two main streams of study in the decision support literature: “distribution” of knowledge among different agents, and “collaboration” of knowledge for reaching a shared goal. This study resulted in identification of two main gaps: first, there is no enough recognition of the technicians’ knowledge; second, there is little assistance for technician by providing the bigger picture. We used cognitive fit theory, and the theory of distributed situation awareness to build the new theoretical model we call the “Distributed Collaborative Awareness Model.” The model considers both explicit and implicit knowledge, and accommodates the dynamic challenges involved in operational level maintenance. As a means of applying this model, we identify and recommend some technological developments required in Augmented Reality based maintenance decision support.

  • 9.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Judgemental errors in aviation maintenance2019In: Cognition, Technology & Work, ISSN 1435-5558, E-ISSN 1435-5566Article in journal (Refereed)
    Abstract [en]

    Aircraft maintenance is a critical success factor in the aviation sector, and incorrect maintenance actions themselves can be the cause of accidents. Judgemental errors are the top causal factors of maintenance-related aviation accidents. This study asks why judgemental errors occur in maintenance. Referring to six aviation accidents, we show how various biases contributed to those accidents. We first filtered aviation accident reports, looking for accidents linked to errors in maintenance judgements. We analysed the investigation reports, as well as the relevant interview transcriptions. Then we set the characteristics of the actions behind the accidents within the context of the literature and the taxonomy of reasons for judgemental biases. Our results demonstrate how various biases, such as theory-induced blindness, optimistic bias, and substitution bias misled maintenance technicians and eventually become the main cause of a catastrophe. We also find these biases are interrelated, with one causing another to develop. We discuss how these judgemental errors could relate to loss of situation awareness, and suggest interventions to mitigate them.

  • 10.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    A prospective study of maintenance deviations using HFACS-ME2019In: International Journal of Industrial Ergonomics, ISSN 0169-8141, E-ISSN 1872-8219, Vol. 74, article id 102852Article in journal (Refereed)
    Abstract [en]

    The factors initiating aviation accidents are usually hidden behind various steps, systems, and tasks, and systematic root-cause analysis is required to uncover the initial factor(s). To reduce the risk of unfavourable events, it is more appropriate to study their causal factors. We argue that an in-depth study on maintenance process deviations could assist in uncovering hidden causal factors. We therefore analyse reported maintenance deviations from an aviation organisation using the Human Factor Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy to aggregate and map hidden causal factors. We find attention and memory errors and inadequacy of processes and documentation are major causal factors. We argue a well-run organisation can capture hidden causal factors and reduce the risk of incidents and accidents. More specifically, we show how situation awareness (SA) interventions can assist in the mitigation of maintenance deviations and capture hidden causal factors.

  • 11.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Identifying significance of human cognition in future maintenance operations2018In: Advances in Intelligent Systems and Computing, ISSN 2194-5357, E-ISSN 2194-5365, Vol. 722, p. 550-556Article in journal (Refereed)
    Abstract [en]

    Industrial maintenance in future will operate heavily with intelligent systems. Advanced sensor networks on machines will enable them communicate and learn about failure types, predict consequences and share solutions. Humans on the other hand are equipped with intuitive cognition that facilitates acquisition of knowledge about unique characteristics of individual machines, and use this knowledge in maintenance problem solving. In this article, we identify two major opportunities to collaborate human intuitive cognition with intelligent systems for future maintenance solutions.

  • 12.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Modelling human cognition of abnormal machine behaviour2019In: Human-Intelligent Systems Integration, ISSN 2524-4876, Vol. 1, no 1, p. 3-26Article in journal (Refereed)
    Abstract [en]

    Despite the advances in intelligent systems, there is no guarantee that those systems will always behave normally. Machine abnormalities, unusual responses to controls or false alarms, are still common; therefore, a better understanding of how humans learn and respond to abnormal machine behaviour is essential. Human cognition has been researched in many domains. Numerous theories such as utility theory, three-level situation awareness and theory of dual cognition suggest how human cognition behaves. These theories present the varieties of human cognition including deliberate and naturalistic thinking. However, studies have not taken into consideration varieties of human cognition employed when responding to abnormal machine behaviour. This study reviews theories of cognition, along with empirical work on the significance of human cognition, including several case studies. The different propositions of human cognition concerning abnormal machine behaviour are compared to dual cognition theories. Our results show that situation awareness is a suitable framework to model human cognition of abnormal machine behaviour. We also propose a continuum which represents varieties of cognition, lying between explicit and implicit cognition. Finally, we suggest a theoretical approach to learn how the human cognition functions when responding to abnormal machine behaviour during a specific event. In conclusion, we posit that the model has implications for emerging waves of human-intelligent system collaboration.

  • 13.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Kumar, Uday
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Sustaining implicit learning in locomotive operation2018In: 20th Nordic Seminar on Railway Technology: Abstracts, Gothenburg, Sweden, 2018, p. 59-Conference paper (Refereed)
    Abstract [en]

    Modern trains are capable of monitoring health status in real time and infer behaviour of various systems. This trend will grow with advancements of machine learning those will produce feedback for continuously improving the prediction models. Despite reduced physical connectivity of human with locomotive systems, human interference will be required for critical decision-making. Human implicit learning involves the largely unconscious learning of dynamic statistical patterns and features, which leads to the development of tacit knowledge1. Pirsig2 argued that “each machine has its own, unique personality which probably could be defined as the intuitive sum total of everything you know and feel about it”. Theses suggest that humans employ an intuitive cognition ability that leads to developing implicit knowledge and interactions with machines. In this study, we focus on signifying the implicit knowledge in locomotive operation context and seek ways to facilitate effective decision-making

  • 14.
    Illankoon, Prasanna
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Tretten, Phillip
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Singh, Sarbjeet
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Decision Support System for Flight Maintenance Technicians: Issues and Challenges2019In: Proceedings of the 5th international workshop and congress on eMaintenace: eMaintenance Trends in technologies & methodologies, challenges, possibilities and applications / [ed] Miguel Casta ̃no Arranz, Luleå, Sweden, 2019, p. 88-94Conference paper (Refereed)
    Abstract [en]

    In this article, we summarize the key insights into the fast-rising areas in decision support and integration of flight maintenance information. The study elaborates the need and challenges of decision support for flight maintenance technicians. The major focus is on the decision support that allows maintenance technicians as end users to interact and get a better understanding of the systems (flights) they are dealing with. 

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