Implementing enterprise resource planning (ERP) systems can be a complex and costly endeavour prone to failure. Hence, it is crucial to identify and manage effective measurement criteria to prevent failure and mitigate negative outcomes during implementation. This study aims to analyse the causal relationships among success measurement criteria within a company engaged in steam boiler construction and production by employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method. The paper integrates theoretical frameworks with practical applications. The authors extracted 15 ERP success measurement criteria through literature review, interviews, and questionnaires. Subsequently, they utilized the DEMATEL method to assess the importance of these criteria and develop causal interrelationships. Utilizing DEMATEL, it categorizes these metrics into cause and effect clusters. Factors like Enterprise Architecture Improvement, Business Process Improvement, and Employee Involvement are deemed causal, while Customer Service Improvement, Workgroup Improvement, and Competitive Model Improvement are categorized as effects. "Enterprise Architecture Improvement" emerges as the most influential criterion. Understanding these metrics and their relationships aids organizations in enhancing ERP capabilities. This research pioneers categorizing ERP success criteria, facilitating more effective implementation. Valuable insights are provided for ERP implementers, consultants, and researchers involved in ERP projects .
Risk assessment is an important factor in project cost management. This study addresses the risks associated with a 900 meter long bridge construction project. The risk of a bridge construction project is assessed to limit and quantify the impact on the project. The impact of various risks was investigated to express the impact on the total project contract value at the estimation stage. A project risk analysis is introduced to assess the percentage of risk attributed to the total cost. After assessing the impact of risks on cost using Expected Monetary Value (EMV), a new approach of including uncertainties on risk analyses, using description (C, Q, K), is discussed and its advantages and shortcomings are highlighted. Risk is then assessed at several stages of project execution during the budgeting phase, and risk-based project value (RPV) is used to assess the value of the project at each stage. RPV usually increases as the project progresses towards its goals. Due to this property, the RPV of the entire project can be categorized into the contribution value (CV) of each activity. The CV of an activity is defined as the increase in RPV after each activity completes successfully. The results highlight the positive impact of successfully completing the activities associated with the highest risk. In addition, practical solutions for risk assessment and analysis of bridge construction projects are provided for use by bridge construction contractors, project managers and project management engineers.
Process capability indices play a vital role in evaluating the conformity of the process properties to the required specifications. Process incapability indices are created by transformation in the process capability indices, leading to the separation of information related to the process accuracy and precision. This separation of information can be very beneficial to specify whether the process is capable or not and to detect deviations in the production processes that produce high-tech products, such as the electronics industry. The main goal of this study is to propose a process incapability index by considering the measurement error for processes with multivariate quality characteristics. The efficiency of this index is then examined by a numerical example using Monte Carlo simulation method. Moreover, the performance of proposed approach is compared with the case where there is no measurement error. In addition, as a practical example, this index is compared with a number of recently proposed indices in the literature, and sensitivity analysis is conducted, as well. The simulation results showed that the measurement error has a significant effect on process capability and incapability indices. Therefore, we strongly suggest that the measurement error has to be considered in the process analysis.
Profile monitoring is one of the new statistical quality control methods used to evaluate the functional relationship between the descriptive and response variables to measure the process quality. Most of the studies in this field concern processes whose response variables follow the normal distribution function, but in many industries and services, this assumption is not true. The presence of outliers in the historical data set could have a deleterious effect on phase I parameter estimation. Therefore, in this paper, we propose a robust cluster-based method for estimating the parameters of generalized linear profiles in phase I. In this method, the effect of data contamination on estimating the generalized linear model parameters is reduced and as a result, the performance of T^2 control charts is improved. The performance of this method has been evaluated for two specific modes of generalized linear profiles, including logistic and Poisson profiles, based on a step shift. The simulation results indicate the superiority of this cluster-based method in comparison to the non-clustering method and provide a more accurate estimation of the parameters.
This work presents a quantitative approach on the basis of Dynamic Bayesian Network to model and evaluate the maintenance of multi-state degraded systems and their functional dependencies. The reliability and the availability of system are evaluated taking into account the impact of maintenance repair strategies (perfect repair, imperfect repair and under condition-based maintenance (CBM)). According to transition relationships between the states modeled by the Markov process, a DBN model is established. Using the proposed approach, a DBN model for a separator Z1s system of Sour El-Ghozlane cement plant in Algeria is built and their performances are evaluated. Through the result of diagnostic, for improving the performances of separator, the components E, R and F should given more attention and the results of prediction evaluation show that in comparing with perfect repair strategy, the imperfect repair strategy cannot degrade the performances of separator, whereas the CBM strategy can improve the performances considerably. These results show the utility of this approach and its use in the context of a predictive evaluation process, which allows to offer the opportunity to evaluate the impact of the decisions made on the future performances measurement. In addition, the maintenance managers can optimize and improve maintenance decisions continuously.
