This paper builds on the previously developed product sustainability index (ProdSI) and process (ProcSI), presents a framework for sustainable manufacturing performance evaluation at systems level. The is then used to propose comprehensive set of metrics enterprise level following five-stage hierarchy (individual metrics, sub-clusters, clusters, sub-index index). 6R concept (reduce, reuse, recycle, recover, redesign remanufacture), total life-cycle emphasis, triple bottom line (TBL) are...

Abstract Society's consumption of natural resources and the impact industrial activities on environment have gained increasing attention over last several decades. This paper provides a historical perspective origins environmental movement its connection to systems. Then, recent research related product design, process improvement change, green manufacturing planning, circular economy are described. With respect topics such as material selection component light-weighting considered. For...

Abstract Over the centuries, application of grassland and cutting livestock have been primary foundations for production food agriculture manufacturing. Growing human population, accelerated activities globally, staggering inequity, changing climate, precise nutrition extended life expectancy, more demand protein call a new outlook to smartness in manufacturing delivering nutritious food. Cellular agriculture, 3-D printing food, vertical urban farming, digital alongside traditional means,...

This paper aims to examine the sustainable manufacturing performance of Reconfigurable Manufacturing Systems (RMSs) using existing metrics. RMS has six key characteristics including modularity, integrability, customization, scalability, convertibility, and diagnosability. In this paper, 'convertibility' is quantified by considering configuration machine material handling device convertibility from perspective. addition, RMSs with different levels also evaluated A numerical example used...

This paper builds on the previously developed maintenance strategy of predictive (PdM) that can detect incipient breakdown a system and determine condition in-service equipment to estimate scheduling. Here, new data-driven model based Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNN) algorithm is proposed degradation manufacturing predict its future health for PdM. To validate accuracy efficiency model, motor bearing failure process used demonstrate method.

Predictive maintenance (PdM) has been widely used in manufacturing to reduce cost and unexpected downtime. A common element within equipment/machines is a motor. This paper aims detect motor faults by collecting analyzing vibration data with wireless sensors. cloud-based condition monitoring system also built the data. An Artificial Intelligence (AI) model trained using collected data, principal component analysis (PCA) utilized abnormal behaviors of Hostelling's T2 statistics squared...

Rare earth elements (REEs) are becoming ever more important and broadly used in rare permanent magnets (REPMs) for electric vehicles, wind turbines, cell phones, etc. While neodymium-iron-boron (NdFeB) very popular, samarium cobalt (SmCo) increasingly being viewed as an alternative REPM option due their better resistance to corrosion oxidation. These properties position SmCo wide use high temperature extreme working environments. As is well known, the availability of REEs many applications...

This study applies design of experiments (DOE) methods in the conduct a techno-economic assessment (TEA) on newly developed rare-earth element (REE) recovery process. The goal this effort is to identify main factors that affect profitability We construct factorial with net profit as response, where experimental data are generated by simulation different scenarios. effects and their interactions determined. Based these results, desirable strategy proposed. It envisioned applied can be...

Thanks to the development of new technologies such as sensor networks and advanced computational power, research field condition-based monitoring (CBM) has drawn increasing attention in manufacturing. With aim enhancing equipment reliability, leading a reduction maintenance costs, one most crucial challenges dealing with CBM is detection or prediction unseen/uncharacterized event during manufacturing system operation. Therefore, identification novel fault conditions learning patterns are...

Generative AI's effect on inclusive education is a revolutionary potential in strengthening the branding strategies of educational institutions dedicated to examined and sustainability. It answers important research questions how generative AI now being used branding, technological settings it provides for students from marginalized backgrounds, benefits problems that come with it. According result, can enhance accessibility through adaptive technologies, personalize outreach tailored...

Abstract Sustainability is a key principle that has been intensely discussed over the past two decades. In this context, sustainable manufacturing, which involves use of processes and systems to produce more products, becoming increasingly important for corporate success. Companies compete globally are required commit report on overall sustainability performance operational initiatives. While variety evaluation methods have presented in literature, manufacturing at enterprise level, none...

A novel design of a vibration energy absorbing mechanism (VEAM) that is based on multi-physics (magnetic spring, hydraulic system, structural dynamics, etc.) for cable proposed. The minimum working force the cylinder has been exploited in this order to combine non-linear stiffness isolation module composed permanent magnetic springs with viscous damping modules. In response different environmental impacts, VEAM can automatically switch control modes without an electronic mechanism....

With view to satisfying customers, it is important correctly ratify importance weights of customer requirements in quality function deployment (QFD). The twenty-first century marked by fast evolution tastes and needs. Customer could vary with time, customers' preferences competitive ability product manufactures. It urgent critical capture the dynamic for new design QFD. To provide an effective method predict requirements, model was proposed forecast based on least square support vector...