An alternate productivity evaluation practice to depict machine guarding performance in a process plant

2nd International Conference on Engineering for Sustainable World

Chukwunedum, Uzor^1 ; Sunday, Oke^2 ; Sociis, Okolie^1

Covenant University, Ota, Nigeria^1

University of Lagos, Yaba, Nigeria^2

关键词: compliance;    Machine compliance;    Operations managers;    Process plants;    Production companies;    Productivity evaluation;    Productivity evaluation models;    Productivity performance;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/413/1/012075/pdf
DOI  :  10.1088/1757-899X/413/1/012075

来源: IOP

【 摘 要 】

Varying from the notion that the significant expenditure channeled on machine guarding has little or no benefit, this paper through an innovated model, argues that the machine guarding productivity could be evaluated for progress in a bottling production company. This paper contributes to the literature on machine guarding by developing a novel variant machine guarding productivity evaluation model which was validated with dataset from a process plant in Nigeria. Well descriptive results from the model shows that when period 5 is compared with period 1, the model showed an increase in % compliance for trip guards, fixed guards and e-stop guards by 2.82%, 1.41% and 2.53% respectively, while the number of functional guards remained unchanged across all guard categories. As a result of the increment in % compliance for the afore mentioned guard categories, there was an increment in machine guard compliance output for the affected guard types, thus a rise in total machine guard compliance output from 985.1 to 993.08. The machine guard productivity for periods one and five showed a 34.54% and 34.01% decrease for the respective periods from the original status. It also reveals a 0.81% change in guard compliance productivity from period 1 to period 5. The model showed the efficiency of the framework in evaluating operator's productivity performance as a useful source of information for operations managers to trace and adjust quantifiable productivity targets of the machine compliance scheme.