Construction projects are conventionally analyzed considering factors such as cost and completion time. The present paper focuses on the projects particularly dealing with the house or building. The paper aims at an objective of introducing a synergy between project and supply chain management. After a brief relevant literature review, major construction activities have been discussed and the associated synergy between project management and supply chain concepts has been explained. Applications of the supply chain concepts such as forward and reverse logistics along with the customer order decoupling point in the context of construction management are discussed as a result of the proposed development. For this purpose, a categorization of construction product is developed on the basis of land and building characteristics and it is the major contribution of the present paper. This is also expected to be useful for estimating lead time and availability of the product in the context of relevant supply chain, and an associated managerial implication.

Wee et al. (2007) developed an optimal inventory model. In this technical note, we point out a contradiction between Wee et al. & apos; s model and their assumption. A corrected model is developed based on their assumption. Numerical examples show that in terms of the two decision variables, there is a significant difference between the corrected model and Wee et al. & apos; s model. The results also show that that the penalty of using Wee et al. & apos; s model can be significant under certain situations.

The aversion dynamics research agenda has incorporated within dispatching heuristics a number of real-world observations involving risk mitigation practices used by real schedulers. One such observation is that schedulers occasionally offload risky jobs from a primary machine to otherwise less desirable machine (older, slower) during periods of peak load to avoid the effects the risky job can have on subsequent jobs. This paper examines this situation within the proportional parallel machine environment. Safety time is used to adjust dispatching priorities of risky jobs to reflect the aversion. The effect of various safety time values on performance is studied. Robust safety time values and/or intervals are identified across a variety of experimental factors related to risk level, percent risky jobs in the job stream, and due date distribution.

Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering different natural phenomena. Teaching-Learning-based optimization (TLBO) is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.

Due to increasing penetration of internet connectivity, on-line retail is growing from the pioneer phase to increasing integration within people & apos; s lives and companies & apos; normal business practices. In the increasingly competitive environment, on-line retail service providers require systematic and structured approach to have cutting edge over the rival. Thus, the use of benchmarking has become indispensable to accomplish superior performance to support the on-line retail service providers. This paper uses the fuzzy analytic hierarchy process (FAHP) approach to support a generic on-line retail benchmarking process. Critical success factors for on-line retail service have been identified from a structured questionnaire and literature and prioritized using fuzzy AHP. Using these critical success factors, performance levels of the ORENET an on-line retail service provider is benchmarked along with four other on-line service providers using TOPSIS method. Based on the benchmark, their relative ranking has also been illustrated.

In this work, Taguchi method is applied to determine the optimum process parameters for turning of AISI 304 austenitic stainless steel on CNC lathe. A Chemical vapour deposition (CVD) coated cemented carbide cutting insert is used which is produced by DuratomicTM technology of 0.4 and 0.8 mm nose radii. The tests are conducted at four levels of Cutting speed, feed and depth of cut. The influence of these parameters are investigated on the surface roughness and material removal rate (MRR). The Analysis Of Variance (ANOVA) is also used to analyze the influence of cutting parameters during machining. The results revealed that cutting speed significantly (46.05%) affected the machined surface roughness values followed by nose radius (23.7%). The influence of the depth of cut (61.31%) in affecting material removal rate (MRR) is significantly large. The cutting speed (20.40%) is the next significant factor. Optimal range and optimal level of parameters are also predicted for responses.

Globalization has put fierce competition for manufacturing managers in terms of flexibility, smaller lead times, competitive costs, etc. To attain these capabilities, manufacturing managers are taking heedless decisions for investing in advanced manufacturing technologies, without measuring their actual effectiveness for their organisations. There is a need to measure the effectiveness of manufacturing systems to make better future policies and investment planning. This paper provides a comprehensive bibliography on the techniques and their rationale in the effectiveness measurement of advanced manufacturing systems. The paper cites 265 articles from a variety of published sources. The list contains published research mainly from 1990 to 2012 and a selected published work prior to 1990.

In general, production system often gets disrupted due to uncertainty and un-planned events, which also affect demands resulting in less abet-margin of a company. With disrupted production system, management would need to study the variation of demand pattern and disruption of system; we have attempted an effort to establish an exponential demand with the production system and solved analytically the problem to determine production time before and after disruptions. Exponentially demand pattern studied, and also we simulate for sensitivity analysis in order to find which parameter is getting significant change for the proposed model.

In this paper, we study no-wait flow shop problem where setup times depend on sequence of operations. The proposed problem considers sequence-independent removal times, release date with an additional assumption that there are some preliminary setup times. There are two objectives of weighted mean tardiness and makespan associated with the proposed model of this paper. We formulate the resulted problem as a mixed integer programming, where a two-phase fuzzy programming is implemented to solve the model. To examine the performance of the proposed model, we generate several sample data, randomly and compare the results with other methods. The preliminary results indicate that the proposed two-phase model of this paper performed relatively better than Zimmerman & apos; s single-phase fuzzy method.

This paper addresses the scheduling of machines, an Automated Guided Vehicle (AGV) and two robots in a Flexible Manufacturing System (FMS) formed in three loop layouts, with objectives to minimize the makespan, mean flow time and mean tardiness. The scheduling optimization is carried out using Sheep Flock Heredity Algorithm (SFHA) and Artificial Immune System (AIS) algorithm. AGV is used for carrying jobs between the Load/Unload station and the machines. The robots are used for loading and unloading the jobs in the machines, and also used for transferring jobs between the machines. The algorithms are applied for test problems taken from the literature and the results obtained using the two algorithms are compared. The results indicate that SFHA performs better than AIS for this problem.