In this paper, an integrated production-inventory model with multi-item is developed from the perspectives of single producer, multiple suppliers and retailers. In this three-layer supply chain, the retailers are non-competing. Every supplier delivers only single type of raw material to the producer. The producer manufactures finished goods from the combination of fixed percentage of different types of raw materials. The producer manufactures various types of objects and supplies them to retailers according to the demand of multiple retailers. This paper studies the impact of different types of business policies such as exponential demand rate, demand dependent production rate, optimum order size of raw materials, and unit production cost at each stage of integrated marketing system. Mathematica is used to develop the model and to optimize the integrated profit function. A numerical example and sensitivity analysis is illustrated to justify the feasibility of the proposed model.

This study investigates optimal pricing and inventory policies for non-instantaneous deteriorating items with permissible delay in payment. The demand rate is as known, continuous and differentiable function of price while holding cost rate, interest paid rate and interest earned rate are characterized as independent fuzzy variables rather than fuzzy numbers as in previous studies. Under these general assumptions, we first formulated a fuzzy expected value model (EVM) and then some useful theoretical results have been derived to characterize the optimal solutions. An efficient algorithm is designed to determine the optimal pricing and inventory policy for the proposed model. The algorithmic procedure is demonstrated by means of numerical examples.

Ti-6Al-4V Extra Low Interstitial (ELI) exhibits superior properties because of controlled interstitial element of iron and oxygen. The effects of four cutting parameters namely cutting speed, feed, depth of cut and tool nose radius on responses like cutting force, average cutting temperature and surface roughness have been investigated for turning of Ti-6Al-4V (ELI). Total 81 experiments have been performed in dry environment. Grey Relational Analysis has been used for multi-objective optimization. Analysis of Variance test has been carried out to investigate contribution of input parameters. The model was found fit with R-Square value of 88.74%. Regression and ANN models are developed for prediction and compared. From the Grey relational analysis, it is clear that optimum parameters to minimize cutting force, cutting temperature and surface roughness while turning Ti-6Al-4V (ELI), are cutting speed as 140 rpm, Nose radius 1.2mm, Feed 0.051mm/rev and depth of cut is 0.5mm. In comparison of regression model, the ANN model is found to be more accurate with average error of 3.57%.

Manpower planning using annualised hours is an effective tool where seasonal demand for staff in industry exists. In annualised hours (AH) workers are contracted to work for a certain number of hours per year. The workers are associated with relative efficiency for different types of tasks. This paper proposes a Mixed Integer linear Programming (MILP) model to solve an annualised working hours planning problem when spike in demand exists. The holiday weeks for the workers are considered as partially individualised. If a worker has been assigned with more than one type of working week in a week, this will be compensated with one or more holiday week. The performance of the model is demonstrated with an example. It can be seen that this type of modelling helps to meet the spikes in demand with less capacity shortage compared with one working week in a week.

Supply chain is a network of organizations that work together and performs various business functions such as procurement of raw materials, converting the raw material into semi-finished or finished goods and distributing the same to their ultimate customers. Presence of bullwhip effect in a supply chain is costly and degrades the performance of the supply chain. Reduction in bullwhip effect can improve the efficiency or profitability of a supply chain. The objective of this paper is to know the impact of imperfect Advance Demand Information (ADI) sharing on bullwhip effect in a four-stage serial supply chain and to evaluate the supply chain performance by conducting an experiment similar to the beer distribution game. The performance measures used are variance of orders placed by each stage, fill rate, total inventory at each stage and total holding cost of the supply chain. Results show that imperfect ADI improves the performance of the supply chain. The performance of the supply chain is also evaluated under order up to level (R, S) policy with safety stock and it is found that the performance of supply chain is better when inventory policy used.

In response to increasing inflexible customer demands and to improve the competitive advantage, industrial organizations have to adopt strategies to achieve cost reduction, continual quality improvement, increased customer service and on-time delivery performance. Selection of the most suitable plant or facility layout design for an organization is one among the most important strategic issues to fulfill all these above-mentioned objectives. Nowadays, many industrial organizations have come to realize the importance of proper selection of the plant or facility layout design to survive in the global competitive market. Selecting the proper layout design from a given set of candidate alternatives is a difficult task, as many potential qualitative and quantitative criteria need to be considered. This paper proposes a Euclidean distance based approach (WEDBA) as a multiple attribute decision making method to deal with the complex plant or facility layout design problems of the industrial environment. Three examples are included to illustrate the approach.

Evaluation of proper supplier for manufacturing organizations is one of the most challenging problems in real time manufacturing environment due to a wide variety of customer demands. It has become more and more complicated to meet the challenges of international competitiveness and as the decision makers need to assess a wide range of alternative suppliers based on a set of conflicting criteria. Thus, the main objective of supplier selection is to select highly potential supplier through which all the set goals regarding the purchasing and manufacturing activity can be achieved. Because of these reasons, supplier selection has got considerable attention by the academicians and researchers. This paper presents a combined multi-criteria decision making methodology for supplier evaluation for given industrial applications. The proposed methodology is based on a compromise ranking method combined with Grey Interval Numbers considering different cardinal and ordinal criteria and their relative importance. A ‘supplier selection index’ is also proposed to help evaluation and ranking the alternative suppliers. Two examples are illustrated to demonstrate the potentiality and applicability of the proposed method.

Continuous generation of electricity of a power plant depends on the higher availability of its components/equipments. Higher availability of the components/equipments is inherently associated with their higher reliability and maintainability. This paper investigates the reliability, availability and maintainability (RAM) characteristics of a 210 MW coal-fired thermal power plant (Unit-2) from a thermal power station in eastern region of India. Critical mechanical subsystems with respect to failure frequency, reliability and maintainability are identified for taking necessary measures for enhancing availability of the power plant and the results are compared with Unit-1 of the same Power Station. Reliability-based preventive maintenance intervals (PMIs) at various reliability levels of the subsystems are estimated also for performing their preventive maintenance (PM). The present paper highlights that in the Unit-2, Economizer (ECO) & Furnace Wall Tube (FWT) exhibits lower reliability as compared to the other subsystems and Economizer (ECO) & Baffle Wall Tube (BWT) demands more improvement in maintainability. Further, it has been observed that FSH followed Decreasing Failure Rate (DFR) and Economizer (ECO) is the most critical subsystem for both the plants. RAM analysis is very much effective in finding critical subsystems and deciding their preventive maintenance program for improving availability of the power plant as well as the power supply.

In this article, a production inventory model is developed to determine the retailer’s optimal replenishment decisions under two levels of trade credit and limited storage space. Two levels of trade credit refers that the supplier provides to his/her retailer a permissible delay period to settle the account and the retailer also in turn provides a delay period to his/her customer for paying of purchasing goods. The retailer’s credit period M offered by supplier is greater than customers credit period N provides by the retailer. This paper investigates retailer optimal replenishment policy under finite replenishment rate by minimizing the total annual inventory cost. Three theorems are developed to determine optimal cycle time, optimal relevant cost and optimal order quantity for retailers accurate and rapidly. A numerical example is used to analyze the validity of propose model, Sensitive analysis shows managerial decisions for retailer.

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.