Green Manufacturing: Relationship between Adoption of Green Operational Practices and Green Performance of Brazilian ISO 9001-Certified Firms

The present work aims at analyzing how the adoption of a proactive environmental management via green operational practices (GOPs) correlates to the Green Performance (GrP) of a given set of ISO 9001-certified firms in Brazil. To this end, we elaborated a conceptual framework about environmental management, GOPs, and GrP Such theoretical foundation supported the development of empirical research through quantitative analysis. For the analysis, 75 questionnaires were collected from ISO 9001 certified companies. Data was analyzed by with statistical tools such as descriptive analysis, correlation analysis, and Structural Equation Modeling (SEM). The results demonstrate that the adoption of GOPs, in fact, exerts a positive impact on the GrP of the firms. This work contributes to a better understanding of green manufacturing in Brazil's industrial sector

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.

Green marketing strategies

This chapter presents the fundamentals of “green” marketing by drawing on traditional marketing theory as well as researchfocused on green marketing context. It discusses five critical areas in green marketing. The first critical area stems from green marketingtheory and practice that examines the logic for reducing the environmental impact of value creation and exchange. The second criticalarea highlights green marketing strategy that focuses on achieving organizational goals in ways that can reduce or eliminate negativeimpacts on the natural environment. The third critical area examines the green marketing mix that accounts for green products, greendistribution, green pricing, and green promotion. By using traditional marketing concepts, the chapter identifies how the entiremarketing mix elements should consistently provide a complete green product offering. Green products and processes need to beresearched, designed, and manufactured to include environmentally safe ingredients and components. Products need to be strategicallypriced to reflect their green values, distributed in the green chain channels and displayed effectively to highlight their status, and accuratelycommunicated to consumers and stakeholders. The fourth critical area illustrates governance and control. It shows how theholistic transformation toward greening the organization requires organizational culture change to gain support within and outside thefirm to ensure environmental issues are appropriately considered. These can be assessed by using existing management mechanisms,such as environmental management systems and/or triple bottom line management, which ensure best practice and continuousimprovements to occur. Lastly, the chapter discusses the future of green marketing and the direction that businesses need to take if theyseek to be sustainable.

Green supply chain management em uma indústria de bens do consumo do Vale do Paraíba - SP

The Green Supply Chain Management (GSCM) is gaining prominence in the academy and business, as an approach that aims to promote economic and environmental gains. The GSCM is operated through the Environmental Management System Tools and treated as an Environmental Management System (EMS), involving Reverse Logistics, Green Purchasing, Green Sourcing, Green Design, Green Packaging, Green Operation, Green Manufacturing, Green Innovation and Customer Awareness. The objective of this study is to map the GSCM tools and identify their practice in a consumer goods industry in the Vale do Paraiba. The approach and data collection were made in the company's database chosen as the object of study, as well as through on site visits and interviews. The results showed that the tools Green Operation, Green Manufacturing, Green Innovation and Green Sourcing are applied in the company and just Costumer Awareness tool showed no practice at all. To other tools was identified ideology or interest of the company in applying them

Green supply chain management em uma indústria de bens do consumo do Vale do Paraíba - SP

The Green Supply Chain Management (GSCM) is gaining prominence in the academy and business, as an approach that aims to promote economic and environmental gains. The GSCM is operated through the Environmental Management System Tools and treated as an Environmental Management System (EMS), involving Reverse Logistics, Green Purchasing, Green Sourcing, Green Design, Green Packaging, Green Operation, Green Manufacturing, Green Innovation and Customer Awareness. The objective of this study is to map the GSCM tools and identify their practice in a consumer goods industry in the Vale do Paraiba. The approach and data collection were made in the company's database chosen as the object of study, as well as through on site visits and interviews. The results showed that the tools Green Operation, Green Manufacturing, Green Innovation and Green Sourcing are applied in the company and just Costumer Awareness tool showed no practice at all. To other tools was identified ideology or interest of the company in applying them

Green operations initiatives in the automotive industry:an environmental reports analysis and benchmarking study

Purpose: The purpose of this paper is to focus on investigating and benchmarking green operations initiatives in the automotive industry documented in the environmental reports of selected companies. The investigation roadmaps the main environmental initiatives taken by the world's three major car manufacturers and benchmarks them against each other. The categorisation of green operations initiatives that is provided in the paper can also help companies in other sectors to evaluate their green practices. Design/methodology/approach: The first part of the paper is based on existing literature on the topic of green and sustainable operations and the "unsustainable" context of automotive production. The second part relates to the roadmap and benchmarking of green operations initiatives based on an analysis of secondary data from the automotive industry. Findings: The findings show that the world's three major car manufacturers are pursuing various environmental initiatives involving the following green operations practices: green buildings, eco-design, green supply chains, green manufacturing, reverse logistics and innovation. Research limitations/implications: The limitations of this paper start from its selection of the companies, which was made using production volume and country of origin as the principal criteria. There is ample evidence that other, smaller, companies are pursuing more sophisticated and original environmental initiatives. Also, there might be a gap between what companies say they do in their environmental reports and what they actually do. Practical implications: This paper helps practitioners in the automotive industry to benchmark themselves against the major volume manufacturers in three different continents. Practitioners from other industries will also find it valuable to discover how the automotive industry is pursuing environmental initiatives beyond manufacturing, apart from the green operations practices covering broadly all the activities of operations function. Originality/value: The originality of the paper is in its up-to-date analysis of environmental reports of automotive companies. The paper offers value for researchers and practitioners due to its contribution to the green operations literature. For instance, the inclusion of green buildings as part of green operations practices has so far been neglected by most researchers and authors in the field of green and sustainable operations. © Emerald Group Publishing Limited.

Análisis de la viabilidad de la implementación de compras verdes en una organización teniendo en cuenta la sustentabilidad en la cadena de suministro

Hoy en día las organizaciones buscan ser más sustentables a través de la implementación de prácticas verdes en cadena de suministro; en este documento se busca analizar y desarrollar diferentes métodos, propuestas y estrategias para la incorporación de estas prácticas a lo largo de la cadena de suministro. Esta investigación se llevara a cabo por medio del estudio de la “guía de trazabilidad: un acercamiento practico hacia el avance sustentable en las cadenas de suministro globales” además de la norma ISO PC 20400.3, obteniendo como resultado una propuesta de integración entre las compras verdes y la trazabilidad en la cadena de suministro. Todo esto con el objetivo de establecer los requerimientos mínimos que debe tener una empresa, así como los pasos a seguir para la ejecución exitosa de un programa de compras verdes.

Microstructure development and solute behaviour in Fe-C and Fe-C-V alloys during strip casting and secondary processing

 Strip casting is a rapid, environment friendly technology for manufacturing thin sheets of steel directly from molten metal. Research presented in this thesis examines the effect of atomic location, cluster size and composition on internal microstructure development during strip casting. Current research potentially leads to green manufacturing of steel.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

A treatise on soap-making : containing an account of the alkaline materials, test for discovering the presence of an alkali, &c. : with full directions for manufacturing yellow, pure, white, and perfumed hard soap : also, complete instructions for the making of green or soft soap, with other requisites necessary to finish the soap-boiler : to which is added, abstracts of the excise laws relative to hard and soft soap-makers /

Mode of access: Internet.

Green supply chain performance measurement using the analytic hierarchy process:a comparative analysis of manufacturing organisations

The main purpose of this research is to develop and deploy an analytical framework for measuring the environmental performance of manufacturing supply chains. This work's theoretical bases combine and reconcile three major areas: supply chain management, environmental management and performance measurement. Researchers have suggested many empirical criteria for green supply chain (GSC) performance measurement and proposed both qualitative and quantitative frameworks. However, these are mainly operational in nature and specific to the focal company. This research develops an innovative GSC performance measurement framework by integrating supply chain processes (supplier relationship management, internal supply chain management and customer relationship management) with organisational decision levels (both strategic and operational). Environmental planning, environmental auditing, management commitment, environmental performance, economic performance and operational performance are the key level constructs. The proposed framework is then applied to three selected manufacturing organisations in the UK. Their GSC performance is measured and benchmarked by using the analytic hierarchy process (AHP), a multiple-attribute decision-making technique. The AHP-based framework offers an effective way to measure and benchmark organisations’ GSC performance. This study has both theoretical and practical implications. Theoretically it contributes holistic constructs for designing a GSC and managing it for sustainability; and practically it helps industry practitioners to measure and improve the environmental performance of their supply chain. © 2013 Copyright Taylor and Francis Group, LLC. CORRIGENDUM DOI 10.1080/09537287.2012.751186 In the article ‘Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations’ by Prasanta Kumar Dey and Walid Cheffi, Production Planning & Control, 10.1080/09537287.2012.666859, a third author is added which was not included in the paper as it originally appeared. The third author is Breno Nunes.

Forward - Green Virtual Enterprises and Their Breeding Environments: Sustainable Manufacturing, Logistics and Consumption

Part 9: Innovation Networks

The impact of gender diversity on performance in services and manufacturing organizations

We present three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction, a negative linear prediction, and an inverted U-shaped curvilinear prediction. The paper also proposes a moderating effect of industry type (services vs. manufacturing). The predictions were tested using archival quantitative data with a longitudinal design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The results help reconcile the inconsistent findings of past research. The findings also show that industry context can strengthen or weaken gender diversity effects.