Industrial and Production Engineering

DEVELOPMENT OF PREDICTIVE MODELS FOR SYNERGISTIC IMPACT OF AGE, PERIOD OF EXPOSURE AND NOISE LEVEL IN QUARRIES ON HEARING THRESHOLD OF WORKERS

2024-04-26T14:41:20Z

DEVELOPMENT OF PREDICTIVE MODELS FOR SYNERGISTIC IMPACT OF AGE, PERIOD OF EXPOSURE AND NOISE LEVEL IN QUARRIES ON HEARING THRESHOLD OF WORKERS ORIOLOWO, Kolawole Taofik Despite the importance of quarry operations to the construction industry in developing countries, the excessive occupational noise involved in quarry operations is a threat to the health of workers. Studies have shown that the age and years of work exposure (YE) are two of the major factors that contribute to auditory health problems among the quarry workers. Information on the effect of noise and related susceptibility factors on hearing damage among Nigerian quarry workers are sparse. This study was conducted to develop suitable models in order to investigate the synergistic influence of age, YE and Noise Level (NL) in quarries on the Hearing Threshold (HT) of workers. Questionnaires were administered to 204 quarry workers, who were randomly selected in the year 2018 from four different quarry sites in southwestern Nigeria, to obtain the age and YE. A follow up study was conducted on 185 of them in 2019. The NL at the quarry sites during the working hours were measured using a digital sound level meter, while an audiogram measured the HT at eight different frequencies (0.25, 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00kHz). Using ANOVA, eight regression models were developed and validated to predict both the effects of age, YE and NL on HT, and the safe HT. These were used to test for both the similarity of the NL conditions in the sites and the predictive significance of the regression model terms. The predictive accuracies of the developed models were evaluated using the predicted R2, while paired sample t-test and correlation statistics were used to ascertain the impact of the workers’ continual exposure to noise within the study period. Analyses were done using t-test at α0.05. The percentage distribution of their age range in years were 9.7% (15-30), 50.8% (31-45), 38.4% (46-60), and 1.1% (60+). The mean age and YE were 42±9.01 and 18±7.03 years, respectively. The NL were in the range of 87.30-116.98dB as against the permissible exposure level of 85.00dB. The NL conditions on the sites were not significantly different (101.61±0.38, 99.28±0.51, 100.51±1.01, 99.28±0.10). The Mean HT of the workers was 45.60±1.24dB and 75.0% of them had HT higher than the safe HT of ≤30.00dB. The age predicted the workers’ HT at all frequencies considered. The YE significantly predicted the HT at 1.00, 2.00, and 4.00 kHz, while NL significantly predicted the HT at 0.25 and 0.50 kHz. The models’ predicted R2 range was 0.71 – 0.82. The safe HT was predicted with age ≤52 years and YE ≤32 years. The validation results were in agreement with the data obtained during the experiment. The correlation and paired sample ranges were 0.17- 0.79 and 6.50-26.7, respectively, which showed that the workers' HT continuously depreciated within the study period. The developed models established that the synergistic factors of age, years of exposure and noise level influenced the hearing threshold of quarry workers. Thus, the models can be used for making decision in achieving workers’ safe operations in quarry industry.

DEVELOPMENT OF A LIFE CYCLE COSTING MODEL FOR LIQUEFIED NATURAL GAS PRODUCTION SYSTEM

2024-04-26T14:36:23Z

DEVELOPMENT OF A LIFE CYCLE COSTING MODEL FOR LIQUEFIED NATURAL GAS PRODUCTION SYSTEM CHARLES, Ebitei Despite the large natural gas reserve in Nigeria and increasing global demand for Liquefied Natural Gas (LNG), prospective investors appear hesitant in doing LNG business in Nigeria. One major reason is that the existing LNG business cost estimation models are inadequate to incorporate various business factors such as long life-span risky events and capital intensiveness. A Life Cycle Costing (LCC) model was developed to accommodate these factors using System Dynamics (SD) principles. Ten LNG business firms operating in Nigeria and abroad were studied and seven randomly selected stakeholders interviewed for insights on LNG business processes. Operating sectors were identified using SD principles. Input and output sector quantities and their inter-relationships were determined using system causal loop, while flow diagramming approach was used to characterise the LNG value chain operations. The LNG-process equations were formulated in terms of plant availability, production workforce capability and shipment delivery rate. These were synthesised to evolve an SD-LNG-LCC model. The model was applied to predict a set of twenty-one year (1999-2019) values of LNG volume shipped and revenue. These were compared to the actual values obtained from an LNG-firm in West Africa. The firm’s LCC, Unit Production Cost (UPC), Return on Investment (ROI), Net Present Value (NPV) and Profitability Index (PI) were also obtained. The viability of the firm’s Greenfield-Brownfield investments and the model’s performance were further evaluated using different scenarios of NG base-prices. Data were analysed using student t-test at α0.05. The identified operating sectors were production, maintenance and finance. Capital and operating expenditures; NG-LNG prices; Train-Capacity; equipment and spares; planned manpower; maintenance-effectiveness; discount-rate, and equipment-failure probabilities were identified sector input quantities, while LCC, production volume, revenue, return on investment, payback period, discounted profit, equipment availability were the outputs. Plant availability, production workforce capability and shipment delivery rate were 0.90, 2310.92 m3gas/man-hour and 6 deliveries/shipyear, respectively. The model predicted LNG volume shipped was (13.46±0.02)×109 tonne per annum (TPA) while the firm’s actual value was (13.62±0.02)×109 TPA. Similarly, the revenue from the predicted and actual were (₦864.00±572.43)×109 [($5.40±3.58)×109] and (₦870.40±561.14)×109 [($5.44±3.51)×109]. These indicated that there was no significant difference between the predicted and actual values. The firm’s LCC, UPC, ROI, NPV and PI were ₦10000.00×109 ($62.50×109), ₦662.40 ($4.14) per MMBTU, 26.01%, ₦2369.60×109 ($14.81×109) and 1.59, respectively. For expansion alternatives, the Greenfield LCC was ₦109264.60 [$682.91] per tonneyear relative to the Brownfield’s ₦76235.20 ($476.47) per tonneyear. In model sensitivity, 50% increase in NG baseprice yielded LCC of ₦7359.80×109 ($45.98×109) compared to ₦12640.20×109 ($79.02)×109 yield by a 150% increase. A liquefied natural gas life cycle costing model was developed using system dynamics principles. The developed model is a useful instrument for determining costs and decision support for liquefied natural gas project investments.

DEVELOPMENT OF HEURISTICS FOR SINGLE PROCESSOR SCHEDULING PROBLEMS WITH TARDINESS - RELATED PERFORMANCE MEASURES

2019-03-22T09:00:09Z

DEVELOPMENT OF HEURISTICS FOR SINGLE PROCESSOR SCHEDULING PROBLEMS WITH TARDINESS - RELATED PERFORMANCE MEASURES AKANDE, SAHEED Scheduling problems involve the processing of jobs on processor(s) subject to constraints to optimise performance measures. Determining schedules that minimise tardiness-related performance measures for single processor scheduling problems is complex. Optimal-solutions require prohibitive-time, therefore heuristics are explored in real-life but effectiveness of existing heuristics is inadequate. The objective of this study was to develop effective heuristics for minimizing tardiness-related performance measures for single processor scheduling problems. Six heuristics were developed and compared to the existing heuristics for minimizing the Total-Tardiness of jobs with Release-Dates (2TRD), Total-Tardiness and Total-Flowtime of jobs with Zero-Release-Dates (3TFZRD) and Total-Tardiness and Total-Flowtime of jobs with Release-Dates (3TFRD). HeuristicI (HeuI) and HeuristicII (HeuII) developed for 2TRD problem were compared to Dynamic Modified Due Date (DMDD). For 3TFZRD problem, heuristicIII (HeuIII) and heuristicIV (HeuIV) developed were compared to heuristicA (HeuA). Generalised Algorithm (GAlg) was compared to heuristicV (HeuV) and heuristicVI (HeuVI) developed for 3TFRD. HeuI and HeuII schedule jobs to reduce lateness. HeuIII and HeuIV reduce waiting-time. HeuV and HeuIV reduce idle-time and waiting-time. Fifty instances each, for problem-sizes (n) from small-sized (5≤n≤10), medium-sized (10