Using the human information-processing model and workload to predict staffing demand: A case study in a petrochemical control room

In many sensitive and sophisticated workplaces, human errors are very important. Many events occur annually around the world is evidence to confirm error due to the data processing operators. The main goal of this study was to investigate human information processing models and workload demands on human operators, then developing a regression model for this purpose. This was a case study. Task analysis of control room members, including shift supervisor, board man, and site man and user instrumentation in this study was investigated. Data collection was performed by interviewing employees using a questionnaire with two parts; the first part was the model of human information processing and the second part was workload NASA–TLX and an appendix of opinions existing staffing level and finally task analysis performed using SPSS 16 – SPSS. There was a correlation between workload and stages of human information processing model such as perception (r=0.65, p<0.01), vocal response (r=0.45, p<0.01) and manual response (r=0.15, p<0.05). Some effective factors on workload were vocal response (β=0.232, p=0.033) and perception (β=0.576, p=0.00). The most important factors in the analysis of anticipation staffing demand were perception (β=2.514, p=0.008), workload (β=1.57, p=0.018) and vocal responses (β=2.428, p=0.01), respectively.Discussion and Increasing concentration and attention and perception skills using psychological measures including decreasing the workload and stress and holding specialized training courses are necessary.