Flow sensors in newspaper production

The paper evaluates potential savings in a newspaper production operation achieved by reducing errors in flow sensor counts at stackers, where newspaper bundles are made for distribution to customers. The reduction in count errors is achieved by installing extra flow sensors at various transfer points in the production flow network and using their counts along with using the deducible information from flow conservation equations.As the product flows in the production network, more diversity within the product line is introduced due to variations in inserts. Stop rules for a product inflowing into multiple reservoirs are developed which would minimize expected over production. More precise projections for product completion times are generated, which allow timely corrective actions.State sensors are installed, which give real time information about state of each equipment as to whether it is in an operational or failed mode. Knowledge of the state of the system provides ability to promptly generate, on a real time basis, alternative system configuration substituting redundant operational units for the failed units.     

Bayesian Estimation for Poisson-exponential Model under Progressive Type-II Censoring Data with Binomial Removal and Its Application to Ovarian Cancer Data

In this article, we propose Maximum likelihood estimators (MLEs) and Bayes estimators of parameters of Poisson-exponential distribution (PED) under General entropy loss function (GELF) and Squared error loss function (SELF) for Progressive type-II censored data with binomial removals (PT-II CBRs). The MLEs and corresponding Bayes estimators are compared in terms of their risks based on simulated samples from PED. The proposed methodology is illustrated on a real dataset of ovarian cancer.     

Interpretive structural modeling-based framework for mass customisation enablers: an Indian footwear case

Abstract

In the epoch of open economy and with the emergence of availability of individualised products over the Internet, Indian manufacturing industries are facing an enormous pressure to become more flexible and responsive, to accomplish customer’s varied and increasing demands. Mass customisation (MC) is about developing a customised product on demand for a particular customer after reception of a real order and producing it with the similar operational efficiency as one would anticipate from a mass-produced product. MC takes into account the merits of both the earlier systems of production, i.e. mass production and craft production. The craft production satisfies the personalised demands of customers and the mass production produces a limited variety of products at lower cost. Industries in developing countries such as India confront pressure from several perspectives to adopt MC. This study has been presented in the context of Indian manufacturing industries, and particularly for footwear industries to examine the enablers of MC. Achieving MC, however, require certain enabling technologies and processes in place. Several such enablers have been identified from the research literature. The objective of this study it to key out significantly important enablers for MC using interpretive structural modelling (ISM), and develop a hierarchy of these enablers for the Indian footwear units. ISM results show that modularity-based practices, digital manufacturing practices and supply chain integration are the most important MC enablers. Enhanced flexibility and responsiveness in the footwear production system can be achieved through modular and reconfigurable production system.     

Risk management in plant investment decisions: risk typology,dimensions and process

Abstract

Managing risk associated with plant location decisions is a growing concern as companies seek to reassure investors about the robustness of their strategies. However, little attention has been paid to the systematic evaluation of risk associated with new plants. This paper investigates risk management practices in plant investment decisions through detailed case investigations in a cross section of industrial businesses at different levels of maturity in order to observe current practices, identify common principles and to synthesis systematic approaches to risk management. It identifies key risk categories and dimensions of risk management, building on three key bodies of literature – global manufacturing, investment and risk management     

Lean road transportation – a systematic method for the improvement of road transport operations

Road transportation has become an important factor in international trade and the management of supply chains. However, this form of product logistics has generally been considered inefficient. Traditionally, practical inefficiencies of road transportation have been addressed through mathematical modelling, operations research-based methods and simulation. This paper presents an alternative systematic approach to improve road transport operations based on lean thinking and the reduction of the seven transportation extended wastes. To do this, the paper reviews the extant literature in the area of lean road transportation, providing a structured research definition of the application of lean thinking in road transport operations and hence guidance on the limited research conducted in this field. The systematic lean transportation method is then presented and empirically tested through a case study in a Mexican firm. The results obtained from the case study indicate that the proposed systematic lean method is an effective alternative for the improvement of road transport operations, with the number of distribution routes and distance travelled being reduced by 27 and 32%, respectively. The proposed method can be used by organisations as a guide to help them improve their road transport operations. In addition, the paper’s aim is to contribute by stimulating scholars to further study the application of lean thinking and waste reduction in road transport operations.     

Transient analysis of an M/M/c queuing system with balking and retention of reneging customers

In this paper, we study an infinite capacity multi-server Markovian queuing system with balking and retention of reneging customers. The transient analysis of the model is performed. The probability generating function technique along with Bessel function properties is used to derive the time-dependent state probabilities explicitly.     

ELICITATION OF SUBJECTIVE PROBABILITIES IN THE CONTEXT OF DECISION-MAKING *

In this paper a framework is developed to seek information from the decision-maker about uncertain events, and to use this information for identifying a preferred alternative. It is shown how a preferred alternative can be identified with less than perfect knowledge of the probabilities.