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Developments in haul road design technology
Published in Vladimír Strakoš, Vladimír Kebo, Radim Farana, Lubomír Smutný, Mine Planning and Equipment Selection 1997, 2020
Roger J. Thompson, Alex Τ Visser
The MMS model program for mine haul roads was developed to evaluate alternative maintenance intervals and the associated effect on total road-user costs, comprising vehicle operating and road maintenance cost elements. Road maintenance costs and fleet productivity was assessed by means of user specified data in conjunction with a basic grader productivity model. An evaluation of the total cost variation with maintenance interval enabled the optimum maintenance interval to be determined, both on a minimum total road-user cost basis and in terms of the operating hours of the available maintenance equipment. When analysing the results of individual mine simulations, the actual mine operating practice was seen to closely resemble that predicted by the model, especially with regard to increased maintenance interval on lightly trafficked roads.
Human Factors and Ergonomics from the Earliest Times to the Present
Published in R. S. Bridger, Introduction to Human Factors and Ergonomics, 2017
The productivity model has a number of limitations. It is only usable in companies or jobs with high absenteeism. It assumes that changes that will increase the scope for productivity gains and savings will do so in practice, that is, productivity will go up and stay up. Tight control over the life of the exercise is needed to implement the changes, control the costs, and demonstrate the benefits. The “time saved” hypothesis is based on simplistic notions such as “time is money.” This may work in rigid production line environments but not in others because workers may perceive sick leave as part of the package and take time-off anyway or in nonpaced jobs; the work may “expand to use up the time available.” In some occupations, it may be possible to postpone work or there may be flexibility in the remainder of the workforce (everyone else has to work harder). In service industries, the penalties of failure to deliver (e.g., patients may have to wait longer to be admitted to hospital) are social rather than financial.
Productivity measurement at the sectoral level: The case of Greek lignite mining
Published in G. N. Panagiotou, T. N. Michalakopoulos, Mine Planning and Equipment Selection 2000, 2018
If more detailed and comprehensive data is made available the formulated Cobb- Douglas model will be more reliable. Moreover, the formulation of other models (e.g. non-parametric models with the aid of Data Envelopment Analysis, DEA) will be useful for checking the consistency of results and having a measurement of technical efficiency (Tsolas 1995b; Tsolas & Panagopoulos 1996; Tsolas 1996b). Another alternative could also be the maximization total productivity model proposed by Sumanth (1984) which is based on the total production cost measurement.
Efficiency and productivity of Nigerian seaports in the pre and post concessioning periods
Published in Maritime Policy & Management, 2021
Ogochukwu Ugboma, Kayode Oyesiku
The frontier productivity model, apart from producing estimates of productive inputs captures the value of efficiency or inefficiency as part of its output. The efficiency values for all ports are then regressed as dependent variable against the determinants of port productivity. To assess the determinants of efficiency and hence the relative operational efficiencies of the ports, a Tobit model is used in estimating the efficiency values obtained from the productivity model in Table 4. The Tobit analysis is ideal in cases where the dependent variable has values that range between 0 and 1. The efficiency values range from 0 to 1. Thus, in the Tobit regression analysis, various input variables were tested namely: number of equipment, number of operational staff, ‘concession effect’ (a dummy variable capturing regimes of pre and post concession introduction) and ship turnaround times (proxy for overall level of service at the port). The results of the Tobit model is presented in Table 5.