Consumer demand for Electric Vehicles (EVs) is increasing due to improving performance and affordability. However, EV manufacturers are struggling meet this rise in demand. A key bottleneck supply from a nascent battery chain that new developing. In paper, we propose robotic work cell design fast reliable assembly of modules, at scale, reduce demand-supply gap.

Manufacturing is undergoing a paradigmatic shift as it assimilates and transformed by machine learning other cognitive technologies. A new paradigm usually necessitates framework to comprehend fully, organise extant knowledge, identify gaps in guide future research practice, synthesise knowledge. Paradoxically, such the practice of ML manufacturing remains absent. This paper attempts fill this gap presenting interpretive model an integrative for manufacturing. systematic hybrid literature...

The COVID-19 pandemic unraveled the weak points in global supply chain for goods. Specifically, people all over world, including those most advanced nations have had to go without medical supplies and personal protective equipment. Scarcity of essentials increases anxiety uncertainty exacerbating unproductive behaviors like hoarding price gouging. Left market forces, such unfair practices are likely aggravate hardships increase loss lives. Thus, there is a critical need ensure safe...

High quality, safe, and reliable batteries are essential for widespread adoption of electric vehicles. Current Li-ion battery pack manufacturing processes rely on manual inspections to ensure vehicle quality. Such quality control is prone errors, increasing the chances defective batteries. This likely increase safety reliability concerns in public imagination, slowing down Furthermore, inspection time-consuming become a bottleneck scaling up production. A potential solution address this need...

A defining feature of the response to COVID-19 pandemic was a pervasive and palpable collapse sense-making in individuals organisations. key factor underlying this chaos inability humans make sense big noisy data environment. Such environments are especially amenable interpretation by Artificial intelligence. In study, theoretical framework has been developed for use AI survival supply chains. The proposed framework, 'The Cognitive Model Survival Supply Chains', is articulated as consisting...

As electric vehicle adoption accelerates and demand increases, the inability to produce batteries in sufficient quantities has emerged as a critical bottleneck supply chain. Given impending climate change crisis, resolving this is imperative accelerate transition zero-emission mobility future. One potential solution use of robotics for fast cost-effective assembly at scale. This study proposes three-stage digital twin design analysis method develop robotic workcells battery modules. Using...

Purpose This paper advances a research agenda for service researchers at the intersection of healthcare and information technologies to improve access quality affordable prices. The article reviews key trends provide an focusing on strategies, governance management processes. Design/methodology/approach synthesizes literature in systems, management, marketing operations suggest agenda. authors draw frameworks such as interpretive model technology, technology acceptance model, assemblage...

The growing abundance of text articles in internet requires automated tagging using key phrases.The phrase generation resources helps the information retrieval.To generate phrases for texts from all possible domains, need is an approach that would extract ideas directly itself.In this paper, we have suggested a methodology uses noun words and phrases, their occurrence co-occurrences to keywords.The method, employing both statistical linguistic features, has been successful extracting...

Cryptocurrencies like Bitcoin have received substantial attention from financial exchanges. Unfortunately, arbitrage-based market price prediction models are ineffective for cryptocurrencies. In this paper, we utilize standard machine learning and publicly available transaction data in blocks to predict the direction of movement. We illustrate our methodology using merged blockchain various online sources. This gave us history (block IDs, block timestamps, senders’ addresses, receivers’...

Organizations have long valued and pursued data analytics. For decades, most firms accumulated vast amounts of data, yet they differ greatly in their capabilities to derive significant busines...

The shift in enterprise applications to disruptive mobile platforms calls for research better understand the mechanisms and factors behind success these new platforms. In this paper, we empirically study learning dynamics of sales officers associated with business value, measured as account-opening efficiency a tablet-based banking application at large private bank an emerging market. Our model allows us individual patterns, our results show that although high performers traditional systems...

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Modularity in products is a well-accepted strategy for diversifying and enabling the development of new products. A modular product not only eases designing, construction, testing products, but also fits well production, distribution, customization cost-effectively. In this study, we propose modularity as keystone progressive fast-evolving, yet nascent electric vehicle (EV) product. Specifically, present conceptual framework cyberinfrastructure-based platform criteria-dependent EV...