The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.

In construction cost management system, normally earned value management (EVM) is applied as an efficient control approach in both status detection and estimation at completion (EAC) cost forecasting. The traditional approaches in EAC predictions normally extend the current situation of a project to the future by employing pervious performance factor. The proposed approach of this paper considers both qualitative and quantitative factors affecting the EAC prediction. The proposed approach of this research not only estimates the completion of the project, but also it can generate accurate forecast for the entire future periods using a fuzzy neural network model. The model is also implemented for a real-world case study and yields encouraging preliminary results.

The fast industrial development increases different types of risks for the industries. Many risk factors are inherent in the implementation of advanced manufacturing technologies (AMTs). Industries are developing methodologies for risk prevention and protection. The present research focuses to identify various risks that could influence the implementation of AMTs, and develop a framework to mitigate them. For this framework, interpretive structural modeling(ISM) has been used to depict the relationship and priority among the various risks. This research provides a path for managers and indicates the dominant risks on the basis of higher driving power. Also, this research classifies the relationship among various risks in AMTs implementation according to their driving power and dependence. The risks have been categorized into four categories as autonomous risks, linkage risks, dependent risks and independent risks. The proposed hierarchal model would help the management to effectively handle and develop strategies against the risks and hence new and latest technologies can be adopted with ease and effectiveness.

This paper studies the problem of single machine stochastic scheduling with random processing times, deterministic due dates and an independent setup time. The jobs are also deteriorated based on the position, which their processes are done. The objective function is to find a schedule of jobs, which minimizes the expected value of maximum lateness. A branch and bound scheme is presented to solve the problem analytically and a simulated annealing meta-heuristic (SA) is also provided for solving the problem in larger scales. Computational experiments demonstrate that the proposed SA is capable of finding near optimal solutions with very low gap.

Highly automated CNC end milling machines in manufacturing industry requires reliable model for prediction of tool flank wear. This model later can be used to predict the tool flank wear (VBmax) according to the process parameters. In this investigation an attempt was made to develop an empirical relationship to predict the tool flank wear (VBmax) of carbide tools while machining LM25 Al/SiCp incorporating the process parameters such as spindle speed (N), feed rate (f), depth of cut (d) and various % wt. of silicon carbide (S). Response surface methodology (RSM) was applied to optimizing the end milling process parameters to attain the minimum tool flank wear. Predicted values obtained from the developed model and experimental results are compared, and error & LT; 5 percent is observed. In addition, it is concluded that the flank wear increases with the increase of SiCp percentage weight in the MMC.

A paper published by Maniya and Bhatt (2011) (An alternative multiple attribute decision making methodology for solving optimal facility layout design selection problems, Computers & Industrial Engineering, 61, 542-549) proposed an alternative multiple attribute decision making method named as “Preference Selection Index (PSI) method” for selection of an optimal facility layout design. The authors had claimed that the method was logical and more appropriate and the method gives directly the optimal solution without assigning the relative importance between the facility layout design selection attributes. This note discusses the mathematical validity and the shortcomings of the PSI method.

This paper presents some findings of Indian manufacturing sectors viz. automobile (especially two-wheeler), tractor and general manufacturing industry. Various manufacturing strategy issues such as competitive priorities, improvement activities, and performance measures, have been identified and assessed in Indian context. Sector wise comparison of competitive priorities, improvement activities i.e. advanced manufacturing technology (AMT), integrated information systems (IIS), and advanced management systems (AMS), and performance measure, is provided. Our results showed that most of the Indian companies are still emphasizing on quality. However, automobile sector has set to compete globally with high innovation rate, faster new product development, and continuous improvement. It is also observed that Indian companies are investing more in AMS as compared to IIS and AMT. Manufacturing competence index is also computed for each sector.

This paper explains theoretical approach of the four theories of General system Theory (GST) developed by Yourdon (1989) [Yourdon, E. (1989). Modern Structured Analysis. Yourdon Press, Prentice-Hall International, Englewood Cliffs, New Jersey. Senge] while applying it in information technology and subsequently used by caddy (2007) [Caddy I.N., & Helou, M.M. (2007). Supply chains and their management: Application of general systems theory. Journal of Retailing and Consumer Services, 14, 319–327.] in field of supply chain and management. JIT philosophy in core activities of supply chain i.e. procurement, production processes, and logistics are discussed through general system theory. The growing structure of the supply chain poses the implication restrictions and requires a heavy support system, many times a compromise is done while implementing JIT. The study would be useful to understand the general trends generated naturally regarding the adoption of the JIT philosophy in the supply chain.

Banks are principally in the interest earning business. The interest earning nature of banks comes with the amount of loans that banks are able to advance to their customers. To ensure that the stream of interest is not treacherous, banks must put in place stringent credit risk management practices. In this study, we investigate credit risk and default among Ghanaian banks and how these banks are coping with such pressures. Using a survey method, we found that though varied in nature, all the banks have some form of credit management procedures put in place to manage their loan portfolios. We found loan application processes to be bank specific. However, there are some common requirements that banks usually demand from customers in the process of assessing their suitability for a loan. We also found most of the credit management practices of banks to be consistent with the CAMPARI model. We recommend that the Central Bank facilitate in the establishment of a vibrant credit-referencing bureau in order to provide credit history of customers of the banks.

This paper investigates the persistence of earnings components and pricing test of abnormal changes in cash for selected firms listed on Tehran Stock Exchange (TSE). The proposed study gathers the necessary data from 166 firms over the period 2004-2012 from firms whose shares were actively traded on TSE market. The study uses Panel data and with the implementation of linear regression technique examines four hypotheses. The results indicate that abnormal negative changes in cash are more persistence than positive abnormal changes. In addition, both positive and negative abnormal changes are more persistence than accruals. Market also has a good perception on abnormal positive and negative changes in cash.