Green manufacturing supply chain design and operations decision support

This special issue of International Journal of Production Research provides a platform for sharing the knowledge base, recent research outputs and a review of recent developments highlighting the critical aspects of green manufacturing supply chain design and operations decision support. The special issue includes 15 contributions presenting new and significant research in the relevant area. Contributions mainly present either a novel green/sustainable manufacturing supply chain design and operations decision support approach applied to a problem, or a state-of-the-art method on green/sustainable factors in supply chain design and operations. The article delineates an overview of the contributions and their significance, and an introspection on the ‘green’ factors involved.

A micro industry with closed energy and water cycles for sustainable rural development

Sustainable development requires combining economic viability with energy and environment conservation and ensuring social benefits. It is conceptualized that for designing a micro industry for sustainable rural industrialization, all these aspects should be integrated right up front. The concept includes; (a) utilization of local produce for value addition in a cluster of villages and enhancing income of the target population; (b) use of renewable energy and total utilization of energy generated by co and trigeneration (combining electric power production with heat utilization for heating and cooling); (c) conservation of water and complete recycling of effluents; (d) total utilization of all wastes for achieving closure towards a zero waste system. Enhanced economic viability and sustainability is achieved by integration of appropriate technologies into the industrial complex. To prove the concept, a model Micro Industrial Complex (MIC) has been set up in a semi arid desert region in Rajasthan, India at village Malunga in Jodhpur district. A biomass powered boiler and steam turbine system is used to generate 100-200 KVA of electric power and high energy steam for heating and cooling processes downstream. The unique feature of the equipment is a 100-150 kW back-pressure steam turbine, utilizing 3-4 tph (tonnes per hour) steam, developed by M/s IB Turbo. The biomass boiler raises steam at about 20 barg 3 tph, which is passed through a turbine to yield about 150 kW of electrical power. The steam let out at a back pressure of 1-3 barg has high exergy and this is passed on as thermal energy (about 2 MW), for use in various applications depending on the local produce and resources. The biomass fuel requirement for the boiler is 0.5-0.75 tph depending on its calorific value. In the current model, the electricity produced is used for running an oil expeller to extract castor oil and the castor cake is used as fuel in the boiler. The steam is used in a Multi Effect Distillation (MED) unit for drinking water production and in a Vapour Absorption Machine (VAM) for cooling, for banana ripening application. Additional steam is available for extraction of herbs such as mint and processing local vegetables. In this paper, we discuss the financial and economic viability of the system and show how the energy, water and materials are completely recycled and how the benefits are directed to the weaker sections of the community.

A framework for enabling dynamic e-business strategies via new enterprise paradigms and ERP solutions

In the global Internet economy, e-business as a driving force to redefine business models and operational processes is posing new challenges for traditional organizational structures and information system (IS) architectures. These are showing promises of a renewed period of innovative thinking in e-business strategies with new enterprise paradigms and different Enterprise Resource Planning (ERP) systems. In this chapter, the authors consider and investigate how dynamic e-business strategies, as the next evolutionary generation of e-business, can be realized through newly diverse enterprise structures supported by ERP, ERPII and so-called "ERPIII" solutions relying on the virtual value chain concept. Exploratory inductive multi-case studies in manufacturing and printing industries have been conducted. Additionally, it proposes a conceptual framework to discuss the adoption and governance of ERP systems within the context of three enterprise forms for enabling dynamic and collaborative e-business strategies, and particularly demonstrate how an enterprise can dynamically migrate from its current position to the patterns it desires to occupy in the future - a migration that must and will include dynamic e-business as a core competency, but that also relies heavily on ERP-based backbone and other robust technological platform and applications.

Estimation of computer waste quantities using forecasting techniques

Technology changes rapidly over years providing continuously more options for computer alternatives and making life easier for economic, intra-relation or any other transactions. However, the introduction of new technology “pushes” old Information and Communication Technology (ICT) products to non-use. E-waste is defined as the quantities of ICT products which are not in use and is bivariate function of the sold quantities, and the probability that specific computers quantity will be regarded as obsolete. In this paper, an e-waste generation model is presented, which is applied to the following regions: Western and Eastern Europe, Asia/Pacific, Japan/Australia/New Zealand, North and South America. Furthermore, cumulative computer sales were retrieved for selected countries of the regions so as to compute obsolete computer quantities. In order to provide robust results for the forecasted quantities, a selection of forecasting models, namely (i) Bass, (ii) Gompertz, (iii) Logistic, (iv) Trend model, (v) Level model, (vi) AutoRegressive Moving Average (ARMA), and (vii) Exponential Smoothing were applied, depicting for each country that model which would provide better results in terms of minimum error indices (Mean Absolute Error and Mean Square Error) for the in-sample estimation. As new technology does not diffuse in all the regions of the world with the same speed due to different socio-economic factors, the lifespan distribution, which provides the probability of a certain quantity of computers to be considered as obsolete, is not adequately modeled in the literature. The time horizon for the forecasted quantities is 2014-2030, while the results show a very sharp increase in the USA and United Kingdom, due to the fact of decreasing computer lifespan and increasing sales.

Non-stationary stochastic inventory lot-sizing with emission and service level constraints in a carbon cap-and-trade system

Firms worldwide are taking major initiatives to reduce the carbon footprint of their supply chains in response to the growing governmental and consumer pressures. In real life, these supply chains face stochastic and non-stationary demand but most of the studies on inventory lot-sizing problem with emission concerns consider deterministic demand. In this paper, we study the inventory lot-sizing problem under non-stationary stochastic demand condition with emission and cycle service level constraints considering carbon cap-and-trade regulatory mechanism. Using a mixed integer linear programming model, this paper aims to investigate the effects of emission parameters, product- and system-related features on the supply chain performance through extensive computational experiments to cover general type business settings and not a specific scenario. Results show that cycle service level and demand coefficient of variation have significant impacts on total cost and emission irrespective of level of demand variability while the impact of product's demand pattern is significant only at lower level of demand variability. Finally, results also show that increasing value of carbon price reduces total cost, total emission and total inventory and the scope of emission reduction by increasing carbon price is greater at higher levels of cycle service level and demand coefficient of variation. The analysis of results helps supply chain managers to take right decision in different demand and service level situations.

Assessing the queuing process using data envelopment analysis:an application in health centres

Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients’ department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages.

Is keiretsu really a source of competitive advantage for Japanese automotive suppliers?

Purpose - The purpose of this paper is to examine how firms create and sustain competitive advantage in the inter-firm business relationships from a supplier's perspective. It also investigates what factors affect their competitiveness and relationship between buyers and suppliers. Design/methodology/approach - This is an exploratory study on keiretsu partnerships composed of four main phases: analysis of theoretical perspectives, construction of a conceptual framework, interview of a CEO, and finally, a survey questionnaire with Japanese automotive suppliers. Findings - As a result, this paper classified these 11 companies into four supplier groups (affiliated or independent Tier 1 suppliers; affiliated or independent Tier 2 suppliers) and analysed their competitiveness developing the research propositions further. The benefits of affiliation under a keiretsu partnership are discussed, showing that there may be little benefit in being an affiliated Tier 1 supplier. Even more critical, the results show that independent Tier 2 supplier may be more competitive than affiliated tier ones. Originality/value - These intriguing results reveal an urgent need of investigating Japanese automotive supply chains from the suppliers' perspectives in the future research. This paper extended the literatures on competitive advantage and business relationships at both theory and managerial practice.

Combined quality function deployment and logical framework analysis to improve quality of emergency care in Malta

Purpose – The purpose of this paper is to develop an integrated patient-focused analytical framework to improve quality of care in accident and emergency (A&E) unit of a Maltese hospital. Design/methodology/approach – The study adopts a case study approach. First, a thorough literature review has been undertaken to study the various methods of healthcare quality management. Second, a healthcare quality management framework is developed using combined quality function deployment (QFD) and logical framework approach (LFA). Third, the proposed framework is applied to a Maltese hospital to demonstrate its effectiveness. The proposed framework has six steps, commencing with identifying patients’ requirements and concluding with implementing improvement projects. All the steps have been undertaken with the involvement of the concerned stakeholders in the A&E unit of the hospital. Findings – The major and related problems being faced by the hospital under study were overcrowding at A&E and shortage of beds, respectively. The combined framework ensures better A&E services and patient flow. QFD identifies and analyses the issues and challenges of A&E and LFA helps develop project plans for healthcare quality improvement. The important outcomes of implementing the proposed quality improvement programme are fewer hospital admissions, faster patient flow, expert triage and shorter waiting times at the A&E unit. Increased emergency consultant cover and faster first significant medical encounter were required to start addressing the problems effectively. Overall, the combined QFD and LFA method is effective to address quality of care in A&E unit. Practical/implications – The proposed framework can be easily integrated within any healthcare unit, as well as within entire healthcare systems, due to its flexible and user-friendly approach. It could be part of Six Sigma and other quality initiatives. Originality/value – Although QFD has been extensively deployed in healthcare setup to improve quality of care, very little has been researched on combining QFD and LFA in order to identify issues, prioritise them, derive improvement measures and implement improvement projects. Additionally, there is no research on QFD application in A&E. This paper bridges these gaps. Moreover, very little has been written on the Maltese health care system. Therefore, this study contributes demonstration of quality of emergency care in Malta.

Uncertain natural frequency analysis of composite plates including effect of noise – A polynomial neural network approach

Acknowledgement SN and SS gratefully acknowledge the financial support from Lloyd’s Register Foundation Centre during this work.

A branch and efficiency algorithm for the optimal design of supply chain networks

Supply chain operations directly affect service levels. Decision on amendment of facilities is generally decided based on overall cost, leaving out the efficiency of each unit. Decomposing the supply chain superstructure, efficiency analysis of the facilities (warehouses or distribution centers) that serve customers can be easily implemented. With the proposed algorithm, the selection of a facility is based on service level maximization and not just cost minimization as this analysis filters all the feasible solutions utilizing Data Envelopment Analysis (DEA) technique. Through multiple iterations, solutions are filtered via DEA and only the efficient ones are selected leading to cost minimization. In this work, the problem of optimal supply chain networks design is addressed based on a DEA based algorithm. A Branch and Efficiency (B&E) algorithm is deployed for the solution of this problem. Based on this DEA approach, each solution (potentially installed warehouse, plant etc) is treated as a Decision Making Unit, thus is characterized by inputs and outputs. The algorithm through additional constraints named “efficiency cuts”, selects only efficient solutions providing better objective function values. The applicability of the proposed algorithm is demonstrated through illustrative examples.

Dynamics of spatial heterogeneity in a landfill with interacting phase densities:a stochastic analysis

A landfill represents a complex and dynamically evolving structure that can be stochastically perturbed by exogenous factors. Both thermodynamic (equilibrium) and time varying (non-steady state) properties of a landfill are affected by spatially heterogenous and nonlinear subprocesses that combine with constraining initial and boundary conditions arising from the associated surroundings. While multiple approaches have been made to model landfill statistics by incorporating spatially dependent parameters on the one hand (data based approach) and continuum dynamical mass-balance equations on the other (equation based modelling), practically no attempt has been made to amalgamate these two approaches while also incorporating inherent stochastically induced fluctuations affecting the process overall. In this article, we will implement a minimalist scheme of modelling the time evolution of a realistic three dimensional landfill through a reaction-diffusion based approach, focusing on the coupled interactions of four key variables - solid mass density, hydrolysed mass density, acetogenic mass density and methanogenic mass density, that themselves are stochastically affected by fluctuations, coupled with diffusive relaxation of the individual densities, in ambient surroundings. Our results indicate that close to the linearly stable limit, the large time steady state properties, arising out of a series of complex coupled interactions between the stochastically driven variables, are scarcely affected by the biochemical growth-decay statistics. Our results clearly show that an equilibrium landfill structure is primarily determined by the solid and hydrolysed mass densities only rendering the other variables as statistically "irrelevant" in this (large time) asymptotic limit. The other major implication of incorporation of stochasticity in the landfill evolution dynamics is in the hugely reduced production times of the plants that are now approximately 20-30 years instead of the previous deterministic model predictions of 50 years and above. The predictions from this stochastic model are in conformity with available experimental observations.

Toledo, locus terribilis. Iglesia y milagro en el De viris illustribus de Ildefonso de Toledo

A mediados del siglo VII, el obispo Ildefonso de Toledo (657-667) elaboró su propio catálogo de hombres ilustres, continuando una tradición cuyos orígenes cristianos se remontaban a Jerónimo en el siglo IV. Sin embargo, en lugar de reproducir los modelos de sus antecesores cristianos, entre los que se incluyen además a Genadio de Marsella e Isidoro de Sevilla, el De viris illustribus de Ildefonso incorporaba cambios significativos en el género. Este artículo estudia el tópico del milagro en el opúsculo toledano con el objetivo de indagar qué tipo de relación estableció la Iglesia visigoda de la segunda mitad del siglo VII con este tipo de fenómenos y qué estrategias elaboró en función de él.

Combined atom probe tomography and density functional theory investigation of the Al off-stoichiometry of κ-carbides in an austenitic Fe-Mn-Al-C low density steel

We report on the investigation of the off-stoichiometry and site-occupancy of κ-carbide precipitates within an austenitic (γ), Fe-29.8Mn-7.7Al-1.3C (wt.%) alloy using a combination of atom probe tomography and density functional theory. The chemical composition of the κ-carbides as measured by atom probe tomography indicates depletion of both interstitial C and substitutional Al, in comparison to the ideal stoichiometric L′12 bulk perovskite. In this work we demonstrate that both these effects are coupled. The off-stoichiometric concentration of Al can, to a certain extent, be explained by strain caused by the κ/γ mismatch, which facilitates occupation of Al sites in κ-carbide by Mn atoms (MnγAl anti-site defects). The large anti-site concentrations observed by our experiments, however, can only be stabilized if there are C vacancies in the vicinity of the anti-site.