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Environmental issues and lack of drinking water have forced researchers to find some alternatives to wastewater treatment. Because dyes are used in a variety of industrial applications such as textile and pharmaceutical, wastewater of these factories leads to several environmental problems. Using catalysis under ultraviolet-irradiation (photocatalysis) is one of the cases that is used in wastewater treatment. The purpose of this work is the photocatalytic degradation of dye (Reactive Red 198) and pharmaceutical (tetracycline) using MIL-53(Fe) and MIL-100(Fe).

In this work, Reactive Red 198 (RR198), an anionic dye and tetracycline as a pharmaceutical are tested with two catalysts, MIL-53(Fe) and MIL-100(Fe). Catalyst synthesis method and characterization were discussed by X-ray diffraction, scanning electron microscopy and Fourier Transform Infrared analyses, and their results are described in detail.

Dye concentration varies among 15, 20, 30 and 40 mg/L for MIL-100(Fe) for which the removal percent is 97%, 94%, 89% and 58% and for MIL-53(Fe), dye concentration increases from 20 to 40, 60 and 80 mg/L, the removal percent of which is 98%, 88%, 75% and 50%. Pharmaceutical degradation by MIL-53(Fe) and MIL-100(Fe) was 75% and 80%, respectively.

Photocatalytic degradation of RR198 and tetracycline using MIL-53(Fe) and MIL-100(Fe) was not studied in detail.

This paper aims to propose a new approach for determining a decoupling point in leagile chain, based on Lean and agile criteria regarding market and customer demands and internal capabilities of the chain with the ultimate goal of fulfilling customer needs and increasing chain profit.

In the new approach, Lean and agile criteria have been defined for assessing the effectiveness and efficiency of supply chain. The efficiency and effectiveness ratios have been calculated for Lean and agile processes using input- and output-oriented Banker, Charnes and Cooper (BCC) methods, respectively. Based on the results, inefficient and ineffective units have been addressed and the decoupling point has been determined.

Findings indicate that the decoupling point can be regarded as a borderline between two strategies of Lean and agile production, and fuzzy decoupling point and lean–agile distance can provide the basis for distinguishing the two strategies.

Determining the decoupling point has an important role in dynamic performance of a supply chain. By the proposed approach, managers can estimate the most probable area for the decoupling point. Moreover, by appropriate determination of decoupling point, an organization can increase its public responsibility by appropriate usage of its resources and responding faster to customers’ requirements.

In this study, in addition to determining a decoupling point in a supply chain with the aim of increasing productivity, the subject of leagile strategy of supply chains has been developed.

The purpose of this paper is to prioritize lean production (LP) and agile production (AP) factors based on costs of quality (COQ).

After literature review, two separated houses of quality (HoQ) have been developed. By the first HoQ, LP and AP factors can be proritized based on prevention and appraisal costs and by the second HoQ, LP and AP factors can be prioritized based on failure costs. The proposed approach has been examined by analyzing data collected from 36 home appliance producers of Isfahan as an industrial province of Iran.

The first HoQ indicates that the highest and the lowest priorities are related to over-production (lean factor) and speed (agility factor), respectively. The second HoQ implies that the highest and the lowest priorities are related to responsiveness (agility factor) and inventory (lean factor), respectively. Quadrant analysis also indicates that defectives and over-processing are the two factors that have the highest priorities based on both failure costs and appraisal and prevention costs. As a major finding, LP factors have strong relationship with prevention and appraisal costs; and AP factors have strong relationship with failure costs.

The proposed approach helps organizations in reducing their costs. By clarifying the relationship of the LP and AP factors and the COQ, managers can determine appropriate strategies with the lowest cost.

The integrated approach of this study has not been applied and studied in the literature. The subject of the relationship of LP and AP and COQ is relatively new, which integrates the two areas of production management and quality management.

The purpose of this paper is to propose an integrative model of leagile production and to examine its influence on the quality of products based on Six Sigma approach.

A new model has been proposed in which the three strategies of postponement, mass customization, and modularization are included together with an executive algorithm. The proposed model has been examined using three main products of the Ghods Manufacturing Group, which is a manufacturer of truck body parts, from March to July 2008. In the case study, upstream and downstream processes (after processes warehousing of the semi‐manufactured parts) have been considered for the implementation of lean and agile production strategies, respectively. The product waiting time in the production section has been considered as the lean production indicator, and the warehousing time in the final warehouse has been considered as the indicator of agile manufacturing. These indicators have been evaluated before and after implementation of the proposed model and the sigma level of the studied processes has been evaluated.

The results imply that the sigma level the product A has been improved by 147 percent considering the first indicator and by 8 percent considering the second indicator. Also, product B has 65 and 47 percent and product C has 65 and 150 percent of improvement considering the two indicators, respectively.

The proposed model has not been implemented in a wide range of operations and has not covered all of the products of the case study. Also, due to the lack of literature on standard criteria for evaluating leagile production, the criterion of the duration of waste has been defined and used for leanness and the duration of final storage has been defined and applied to assembly line based on specific orders from customers, which in turn might be realized as a limitation. In comparing the process before and after improvement, there might exist other unknown factors by which, results would be affected.

While the literature includes researches on leagile production and its advantages, this investigation further proposes a leagile production model which includes three strategies of postponement, mass customization, and modularization and is employed based on Six Sigma approach.

The research aims to analyze the effects of financial policies on a cash flow system to meet project performance goals and improve profitability. The policies are divided into four groups; owner related, bank-related, labor-related and supplier-related policies. This research presents a developed model for planning, forecasting and managing the cash flow in construction projects using system dynamics (SD).

A System Dynamics (SD model is developed to evaluate the effect of different financial policies on construction project performance. By identifying the feedback loops in the cash flow system, a dynamic model is developed to forecast, plan and manage different policies, including prepayment, overbilling, loans, incentive payment, delay in payment and equipment lease.

A case study (a construction activity as part of a pharmaceutical factory development project) is used to analyze the cash flow and financing policies. The findings demonstrate the effects of different policies such as incentive payments on project cash flow estimation, which proved to reduce the project duration, improve the profit and increase the financing during the project execution.

The presented model would be a major attempt to estimate precisely the cash flow and the effect of employing different financial policies on project performance. Applying this model, project managers and decision-makers have the opportunity to model different financial policies concerning a variety of limiting variables applicable to each situation. Ultimately, with this, one can make more reasoned decisions and, in effect, optimize the utility of the project.

The paper aims to report a fire test conducted on a three-dimensional frame in order to investigate the behaviour of bare steel flush end-plate connections with relatively low thickness at elevated temperatures.

A half-scale model was fabricated and exposed to modified (scaled) ISO 834 heating curve using a semi-open furnace. The maximum temperature inside the furnace reached 1,026 °C.

The rotations of connections are reported and compared with those of a previous study on an exactly the same model with thick end-plates. Various modes of failure such as local buckling of the beams flanges and lateral-torsional buckling of beams were observed during the test. Finally, the structure collapsed after 29 min of heating due to the fracture of weld between one of the beams and one of its attached end-plates whilst the other beam had undergone a maximum deflection of 35 cm (≈ 1/6 span length). Other observed failure modes included bolt fracture, bolt thread stripping and large inelastic deformation of the end-plates.

Although the adoption of thin end-plates increased the rotational capacity of the connections, it did not improve the robustness of the structure under fire conditions.

Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive review on the use and application of MCDM approach and its associated case studies in the field of MSS.

The paper systematically classifies the published literature of both researchers and practitioners and then analyzes and reviews it methodically.

This paper outlines the important issues relevant to the subject, including the techniques used for data collection, the quantitative and qualitative criteria taken into account in decision making, the maintenance strategies considered for evaluation, the methods applied to find the solution, and the type of industries being studied. In each category, the gaps are identified along with recommendations for the future research work.

Literature on classification of the MCDM models used to select the most appropriate maintenance strategy is very limited. The proposed classification scheme not only will be useful to researchers, but also assists maintenance professionals to find the models that fit their specific needs.

The paper provides many references in the field, including the articles published in academic journals, conference papers, master and doctoral dissertations, text books, and industrial reports, and suggests a classification scheme according to various attributes.

The purpose of this paper is to identify and describe the influence of the knowledge base (KB) of the company on driving forces of innovation processes in knowledge-intensive services (KIS) and to compare the level of innovativeness of the final services.

The paper investigates through qualitative research 11 KIS organisations with different KB.

The research results identified and described the influence of the KB on driving forces of innovations processes and its results in companies with four newly identified KBs (analytical, synthetic, symbolic and compliance).

Further research, based on a larger number of companies, is needed to confirm the results of this research and to complement the effect of the KB on driving forces of innovation.

This research can help organisations understand how to develop strategic plans and new ideas for innovative services depending on the KB of the organisation.

The description of successful innovation processes and results in several leading companies presented in the study may help other companies in identifying knowledge-integration practices to improve performance and innovation processes that support multiplicity, productivity and creativity.

The study systemised the sources of new ideas for innovation in companies with different KB, several driving forces of innovation were identified and how these forces are affected by each KB; lastly, innovation results were compared in companies with different KB.

This paper aims to propose an integrative economic model of the GRI (Global Reporting Initiative) and performance prism based on concurrent engineering and developed balanced scorecard (BSC).

In this paper, the supplier aspect added to the basic BSC framework, a quality function deployment (QFD) developed in four phases and the economic GRI priorities were determined. Finally, the outcomes of QFD were used in Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for ranking the economic indicators.

The indicators of financial interpretation, risks and opportunities had the first rank in learning and growth, internal processes, customer and financial BSC aspects, and they had the second rank only in the suppliers' BSC aspect.

In this paper, merely the economic indicators of the GRI standard was studied, and no comparison was made between the variables of the other standards and the GRI standard.

The most important contribution of this study is merging the supplier aspect and BSC based on the concept of suppliers, inputs, process, outputs and customers (SIPOC) in supply chain analysis. Achieving economic sustainability by a concurrent engineering approach is another novelty of this paper. The proposed model was examined in the tile and ceramic industry for the first time.

This paper aims to use artificial neural networks to develop models for forecasting energy demand for Australia, China, France, India and the USA.

The study used quarterly data that span over the period of 1980Q1-2015Q4 to develop and validate the models. Eight input parameters were used for modeling the demand for energy. Hyperparameter optimization was performed to determine the ideal parameters for configuring each country’s model. To ensure stable forecasts, a repeated evaluation approach was used. After several iterations, the optimal models for each country were selected based on predefined criteria. A multi-layer perceptron with a back-propagation algorithm was used for building each model.

The results suggest that the validated models have developed high generalizing capabilities with insignificant forecasting deviations. The model for Australia, China, France, India and the USA attained high coefficients of determination of 0.981, 0.9837, 0.9425, 0.9137 and 0.9756, respectively. The results from the partial rank correlation coefficient further reveal that economic growth has the highest sensitivity weight on energy demand in Australia, France and the USA while industrialization has the highest sensitivity weight on energy demand in China. Trade openness has the highest sensitivity weight on energy demand in India.

This study incorporates other variables such as financial development, foreign direct investment, trade openness, industrialization and urbanization, which are found to have an important effect on energy demand in the model to prevent underestimation of the actual energy demand. Sensitivity analysis is conducted to determine the most influential variables. The study further deploys the models for hands-on predictions of energy demand.