Abstract:
Energy and Time efficiencies are important factors to lumber production in sawmills. General inefficiencies, such as energy waste and idle time jeopardise sustainability of the sawmill industry. For effective evaluation of energy and time in lumber production, there is need to identify critical factors determining Energy Efficiency (EE) and Time Efficiency (TE). However, there is limited information on the roles of time and energy efficiencies in lumber production in Nigeria. Therefore, this study was conducted to investigate critical factors determining EE and TE during lumber production in Ondo and Ekiti States.
Ondo and Ekiti States were randomly selected among timber producing states in Southwestern Nigeria. Seventeen functional sawmills were purposively selected in Ondo (n = 10) and Ekiti (n=7) States, and 12 logs were randomly selected in each sawmill. Characteristics of sampled logs were determined to provide information onLog Diameter Classes (LDC: small<40; medium- 40.1-65; large>65.1 cm), Log Forms (FL: straight, tapered, crooked) and Frequency Distribution of the Species (FDS). Data on the log parameters: Log Diameter (LD, m), Log Volume (LV, m3), Lumber Recovery (LR, %) were obtained from the processed logs. Idle Energy (IE, kwh), Wood Conversion Rate (WCR, min./m3), Idle Time (IT, min.) Total Time (TT, min.), Sawing Pattern (SP), Product Mix (PM) and Energy Consumption Rate (ECR, kwh/m3) were also determined using standard methods. Structured questionnaire was administered on five respondents: Manager (1), Headrig operator (2), Saw Technician (1) and Timber contractor (1) in each sawmill for information on Age of Machine (AM, yr.),Experience of Headrig Operator (EHO, yr.) and Labour Force (LF). Data were analysed using descriptive statistics, regression and ANOVA at ∝_0.05
The small, medium and large LDC were 11% , 45%and 44% respectively while 29% of the logs were straight, 61% tapered and 10% crooked. A total of 196 logs comprising 24 species were sawn. Ceibapentandrawas the most sawn species, (FDS 24) while Funtumiaelasticahad the least (1). The mean LD: 0.69±0.3, 0.64 ±0.01; LV: 0.73 ±0.12m 0.70±0.06; LR: 50.6± 1.2, 51.5±0.2; AM: 10.01±1.3, 8.22±1.5; EH0:8.78±0.03, 8.1±0.13; and LF: 3.87±0.32, 3.53± 0.33 were obtained for Ondo and Ekiti States, respectively. There were no significant differences in WCR and ECR within and between sawmills in Ondo and Ekiti States. The LV, SDV, EHO and IE had significant positive effect while AM had significant negative effect on EE (R2=0.83) in sawmills in the study area. Also, TT and SP had significant positive effect while IT, AM and PM had significant negative effect on TE (R2=0.54) in sawmills in the study area.
Age of Machine had a negative influence on Energy and Time efficiency; hence old machines should be replaced with newer ones to enhance Energy and Time efficiency. Also effective supervision of workers during log conversion will reduce Idle Time and in effect lead to higher Time Efficiency.
