Selecting lighting system based on workers’ cognitive performance using fuzzy best–worst method and QUALIFLEX

Abstract

The present study aimed to evaluate different illumination systems in the control room of a power plant and decide on the optimal illumination system in terms of the operator’s cognitive performance. This study was conducted on a control room, consisting of 16 operators. The cognitive performance and sleepiness of the subjects were evaluated under three illumination systems: fluorescent lamps (230 lux); fluorescent lamps and LEDs (415 lux), and LEDs (210 lux). The weights of the criteria determined by the FBWM and systems were ranked using the QUALIFLEX. In the morning shift, the simple cognitive function (FDST) and the complex cognitive function (BDST) indices for the fluorescent and LED-illumination system showed the best values. In addition, in the evening shift, the FDST index for the fluorescent and LED-illumination system and the BDST index for the fluorescent illumination system showed the best values. Results related to the weight of each criterion indicated that BDST with the weight of 0.665 is the most important criterion, and then FDST, with the weight 0.2, was placed at ranks 2. The results of this study showed that the best cognitive performance for control room operators provided by combined fluorescent and LED-illumination systems in the morning and fluorescent system in the evening. It is suggested that more appropriate conditions should be provided for individuals in terms of cognitive performance by adding LEDs to the traditional fluorescent systems in the control rooms and setting the appropriate time for the use of LED lamps.

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Availability of data and material

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

LED:

Light-emitting diode

AHP:

Analytic hierarchy process

ANP:

Analytic network process

TOPSIS:

Technique for order preference by similarity to ideal solution

FBWM:

Fuzzy best–worst method

QUALIFLEX:

Qualitative flexible multiple criteria method

FDST:

Forward digit span task

BDST:

Backward digit span task

KSS:

Karolinska sleepiness scale

References

  1. Blackburn HL, Benton AL (1957) Revised administration and scoring of the digit span test. J Consult Psychol 21(2):139

    Google Scholar 

  2. Brennan TA, Leape LL, Laird NM, Hebert L, Localio AR, Lawthers AG et al (1991) Incidence of adverse events and negligence in hospitalized patients: results of the Harvard Medical Practice Study I. N Engl J Med 324(6):370–376

    Google Scholar 

  3. Clark WW, Bohne BA (1999) Effects of noise on hearing. JAMA 281(17):1658–1659

    Google Scholar 

  4. de Korte EM, Spiekman M, Hoes-van Oeffelen L, van der Zande B, Vissenberg G, Huiskes G et al (2015) Personal environmental control: effects of pre-set conditions for heating and lighting on personal settings, task performance and comfort experience. Build Environ 86:166–176

    Google Scholar 

  5. Dumont M, Benhaberou-Brun D, Paquet J (2001) Profile of 24-h light exposure and circadian phase of melatonin secretion in night workers. J Biol Rhythms 16(5):502–511

    Google Scholar 

  6. Folkard S, Lombardi DA, Tucker PT (2005) Shiftwork: safety, sleepiness and sleep. Ind Health 43(1):20–23

    Google Scholar 

  7. Gan J, Zhong S, Liu S, Yang D (2019) Resilient supplier selection based on fuzzy BWM and GMo-RTOPSIS under supply chain environment. Discret Dyn Nat Soc 2019:1–14

    MathSciNet  Google Scholar 

  8. Goel N, Rao H, Durmer JS, Dinges DF (2009) Neurocognitive consequences of sleep deprivation. Semin Neurol 29(4):320–399

    Google Scholar 

  9. Guo S, Zhao H (2017) Fuzzy best-worst multi-criteria decision-making method and its applications. Knowl-Based Syst 121:23–31

    Google Scholar 

  10. Habibi E, Dehghan H, Yazdanirad S, Lotfi S, Hassanzadeh A (2017) The impact of lighting on accuracy and pace of working among men student by tests of job skill assessment under experimental condition. Int J Occup Hyg 9(1):33–37

    Google Scholar 

  11. Hawes BK, Brunyé TT, Mahoney CR, Sullivan JM, Aall CD (2012) Effects of four workplace lighting technologies on perception, cognition and affective state. Int J Ind Ergon 42(1):122–128

    Google Scholar 

  12. Huiberts L, Smolders K, De Kort Y (2015) Shining light on memory: effects of bright light on working memory performance. Behav Brain Res 294:234–245

    Google Scholar 

  13. Hwang C-L, Lai Y-J, Liu T-Y (1993) A new approach for multiple objective decision making. Comput Oper Res 20(8):889–899

    MATH  Google Scholar 

  14. Hygge S, Knez I (2001) Effects of noise, heat and indoor lighting on cognitive performance and self-reported affect. J Environ Psychol 21(3):291–299

    Google Scholar 

  15. Ji P, Zhang H, Wang J (2018) A fuzzy decision support model with sentiment analysis for items comparison in e-Commerce: the case study of PConline.com. IEEE Trans Syst Man Cybern Syst. https://doi.org/10.1109/TSMC.2018.2875163

    Article  Google Scholar 

  16. Juslén H, Tenner A (2005) Mechanisms involved in enhancing human performance by changing the lighting in the industrial workplace. Int J Ind Ergon 35(9):843–855

    Google Scholar 

  17. Kaida K, Takahashi M, Åkerstedt T, Nakata A, Otsuka Y, Haratani T et al (2006) Validation of the Karolinska sleepiness scale against performance and EEG variables. Clin Neurophysiol 117(7):1574–1581

    Google Scholar 

  18. Karapetrovic S, Rosenbloom E (1999) A quality control approach to consistency paradoxes in AHP. Eur J Oper Res 119(3):704–718

    MATH  Google Scholar 

  19. Küller R, Ballal S, Laike T, Mikellides B, Tonello G (2006) The impact of light and colour on psychological mood: a cross-cultural study of indoor work environments. Ergonomics 49(14):1496–1507

    Google Scholar 

  20. Lin CJ, Feng W-Y, Chao C-J, Tseng F-Y (2008) Effects of VDT workstation lighting conditions on operator visual workload. Ind Health 46(2):105–111

    Google Scholar 

  21. Lin CJ, Yenn T-C, Jou Y-T, Hsieh T-L, Yang C-W (2013) Analyzing the staffing and workload in the main control room of the advanced nuclear power plant from the human information processing perspective. Saf Sci 57:161–168

    Google Scholar 

  22. Mohammad Fam I, Zokaei H, Simaei N (2007) Epidemiological evaluation of fatal occupational accidents and estimation of related human costs in Tehran. J Zahedan Univ Med Sci Health Serv 8(4):299–307

    Google Scholar 

  23. Nabil A, Mardaljevic J (2006) Useful daylight illuminances: a replacement for daylight factors. Energy Build 38(7):905–913

    Google Scholar 

  24. Paelinck JH (1978) Qualiflex: a flexible multiple-criteria method. Econ Lett 1(3):193–197

    MathSciNet  Google Scholar 

  25. Peng H-g, Wang J-q (2018) Outranking decision-making method with Z-number cognitive information. Cognit Comput 10(5):752–768

    Google Scholar 

  26. Qin YX, Lin DY, Hui SYR (eds) (2009) A simple method for comparative study on the thermal performance of light emitting diodes (LED) and fluorescent lamps. In: 2009 Twenty-Fourth Annual IEEE Applied Power Electronics Conference and Exposition, pp 15–19

  27. Reason J (2000) Human error: models and management. BMJ 320(7237):768–770

    Google Scholar 

  28. Rezaei J (2015) Best-worst multi-criteria decision-making method. Omega 53:49–57

    Google Scholar 

  29. Roy B (1990) The outranking approach and the foundations of ELECTRE methods. In: Readings in multiple criteria decision aid. Springer, Berlin, Heidelberg, pp 155–183

    Google Scholar 

  30. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15(3):234–281

    MathSciNet  MATH  Google Scholar 

  31. Saaty TL (1996) Decision making with dependence and feedback: the analytic network process. RWS Publications

  32. Salthouse TA (1990) Working memory as a processing resource in cognitive aging. Dev Rev 10(1):101–124

    Google Scholar 

  33. Smith L, Folkard S, Tucker P, Macdonald I (1998) Work shift duration: a review comparing eight hour and 12 hour shift systems. Occup Environ Med 55(4):217–229

    Google Scholar 

  34. Smolders KC, de Kort YA (2014) Bright light and mental fatigue: effects on alertness, vitality, performance and physiological arousal. J Environ Psychol 39:77–91

    Google Scholar 

  35. Terán-Pérez GJ, Ruiz-Contreras AE, González-Robles RO, Tarrago-Castellanos R, Mercadillo RE, Jiménez-Anguiano A et al (2012) Sleep deprivation affects working memory in low but not in high complexity for the n-back test. Neurosci Med 3(4):380–386

    Google Scholar 

  36. Ukai K, Howarth PA (2008) Visual fatigue caused by viewing stereoscopic motion images: background, theories, and observations. Displays 29(2):106–116

    Google Scholar 

  37. Veitch JA, Gifford R, Hine DW (1991) Demand characteristics and full spectrum lighting effects on performance and mood. J Environ Psychol 11(1):87–95

    Google Scholar 

  38. Wolska A (2003) Visual strain and lighting preferences of VDT users under different lighting systems. Int J Occup Saf Ergon 9(4):431–440

    Google Scholar 

  39. Yam F, Hassan Z (2005) Innovative advances in LED technology. Microelectron J 36(2):129–137

    Google Scholar 

  40. Zakerian SA, Yazdanirad S, Gharib S, Azam K, Zare A (2018) The effect of increasing the illumination on operators’ visual performance in the control-room of a combined cycle power plant. Ann Occup Environ Med 30(1):56

    Google Scholar 

  41. Zare A, Yazdani Rad S, Dehghani F, Omidi F, Mohammadfam I (2017) Assessment and analysis of studies related human error in Iran: a systematic review. J Health Saf Work 7(3):267–278

    Google Scholar 

  42. Zare A, Malakouti Khah M, Garosi E, Gharib S, Zakerian SA (2018) The effect of increased light intensity on workload, sleepiness, eye fatigue, and the degree of satisfaction of individuals from the light conditions in the control room of a power plant. J Health Saf Work 8(3):237–250

    Google Scholar 

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Acknowledgements

The authors would like to acknowledge the support and assistance provided by all the participants, who collaborated in this study.

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Authors

Contributions

MA managed and planned the project. MM as a statistician, he re-checked statistical analysis and fixed all the bugs. AZ collected the data in the field, and was a major contributor in writing the manuscript. All authors read and approved the final manuscript.

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Correspondence to Moslem Alimohammadlou.

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Ethics approval was obtained by ethics committee of Shiraz University of Medical Sciences (SUMS).

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Zare, A., Malakoutikhah, M. & Alimohammadlou, M. Selecting lighting system based on workers’ cognitive performance using fuzzy best–worst method and QUALIFLEX. Cogn Tech Work 22, 641–652 (2020). https://doi.org/10.1007/s10111-019-00593-0

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Keywords

  • Lighting
  • Cognitive performance
  • Decision-making methods
  • FBWM
  • QUALIFLEX