Análisis de las características y los módulos que posee Moodle

Literature shows that estimation of product, process and resource cost has been mainly achieved through traditional cost accounting methods usually led by Accountants, Business Administrators and Economists (E. Shehab & Abdalla, 2002; Son, 1991).

intended for management and financial appraisal and do not directly reflect the cost implication of engineering decisions (Agyapong-Kodua, Asare, & Ceglarek, 2014; Johnson & Kaplan, 1987; Maskell, 1991). Consequently, current generation independent cost accounting models perform less well when applied to dynamic product and process design scenarios (Agyapong-Kodua & Weston, 2010). A typical scenario is in the space industry on continual cost overruns of engineering projects, an issue which has existed for the last 40 years although there are better databases, models, estimators, and more stringent reviews (Arthur et al., 2004). According to audit experts on such industry, such as US General Accountability Office, who track cost performance there is difference between models for predicting cost at the inception of projects and those for project implementation (ref). This raised arguments where some are in support of the accuracy of the costing tools and models yet accepts the fact that essential cost elements are omitted whereas others disagree and argue that the tools used are inadequate and a better approach to costing is needed (Keller, et al., 2014). More critically, at early stages of engineering product design, designers need to understand the cost implication of their decisions. Engineering decisions based on CAD models can relate to tolerances, materials selection, dimensions, speed, assembly sequence, cycle time, etc. Traditional cost accounting does not provide formalisms for such micro level cost estimation and it currently rests on the experience of the engineer. The situation becomes more challenging, when there are different technical options to choose from. Under such situations, there must be a fair balance of technical and economic indices and a confirmation of which outcomes to trade-off. This is where cost engineering knowledge becomes very useful. Also in establishing budgets for technical projects, preparation and evaluation of price proposals, contract negotiations and assessing the cost impact of introducing engineering changes to existing designs. To achieve these, cost engineering techniques attempt to capture practical experience, analyse the experience in order to develop tools and models which, together with expert judgement, can be applied under different circumstances to make predictions of likely cost or assessments of whether a proposed cost is reasonable (David, Herve, & Cahill, 2003). Many authors (Johnson & Kaplan, 1987; E. Shehab & Abdalla, 2002; Son, 1991) have argued that cost engineering mainly focusses on cost estimation and control but latest research activities from the cost

engineering domain has shown that cost engineering extends beyond estimation and assessment of cost but includes engineering knowledge which in general terms can help achieve cost effective solutions. Nonetheless, there is the need for scientific methods and techniques to support cost engineering activities so that timely and relevant results can be generated at all times (Agyapong-Kodua, Wahid, & Weston, 2011; Rush & Roy, 2001b). In view of this some researchers in enterprise and systems engineering domains (Kwabena Agyapong-Kodua, J.O Ajaefobi, & R H Weston, 2009; Baines, Harrison, Kay, & Hamblin, 1998; Bernus & Nemes, 1996; Kosanke, 1996; Weston, 1999) have indicated that there is the need for well-structured process- based models to support in-depth analysis.

In recent times, cost engineering principles and modelling methods have been applied by some researchers to support cost estimation, business analysis and planning, project management, profitability analysis and scheduling of major engineering projects (K. Agyapong-Kodua, J. O. Ajaefobi, R. H. Weston, & S. Ratchev, 2012; Agyapong- Kodua, Asare, et al., 2014; R Curran, S Raghunathan, & M Price, 2004; Tammineni, Rao, Scanlan, Reed, & Keane, 2009). Many researchers (Agyapong-Kodua, 2009a; Agyapong-Kodua, Asare, et al., 2014; Agyapong-Kodua & Weston, 2010; Curran, Watson, Cowan, Mahwinney, & Raghunathan, 2003; Roy & Palacio, 2000; Rush & Roy, 2000a) have indicated that to overcome the limitation of cost estimation imposed by traditional cost accounting techniques as well as meeting time deadlines, there might be the need for (1) first sight estimate (suitable for ‘Rough Order Magnitude’ and (2) detailed estimate for precision costing.

More critically, in general terms, companies are expected to meet customers’ requests for quotation in a more efficient and faster manner. The ability to satisfy such requirements is an enabler for good competition and usually a determinant for a company to survive economically. Meeting the requirement for product or project quotation is usually faced with the problem of over or underestimation since in most cases, actual manufacturing systems behaviour or capacity to meet customers’ requirements cannot be fully estimated at an early stage of product development. This

predict cost within reasonable limits of accuracy partly determines an industries (particularly for engineer-to-order enterprises) ability to maintain the lead in product development. In view of cost estimations, underestimation may result in an industry losing money whilst overestimation may result in loss in competition (Veeramani and Joshi, 1996). For these reasons, industries strongly desire a fairly accurate cost estimation solution in support of design activities. Wierda, (1990) concludes that proper costing models can successfully improve the performance of these two strategic functions of organisations. Also, traditional approach to product design and analysis usually requires a designer to first develop a design solution which is then passed on to manufacturers and process designers to provide input into the manufacturing feasibility. When the product designer and manufacturers have agreed on a common solution then the design is passed onto an estimator to calculate the cost of implementing the solution. This can make the design cycle very long and expensive since a lot of decisions would have been confirmed already before passing on the design to the estimator (Rush & Roy, 2000b).