• Ultrasound is an effective eco-friendly technology that enhances the efficiency of various food processes. • It is a substitute for many heat-based, conventional technologies that are detrimental to the product quality. • Ultrasound becomes more powerful when used in combination with conventional processing techniques. • Ultrasound assented unit operation reduces the processing time.

The novel COVID-19 has emerged as a severe threat to global health globally, affecting over 210 countries and regions. The profound dilemma interrupted global trade and social activities and enormously influenced daily lives through social distance and confinements. The outbreak of COVID-19 has exacerbated human misery due to the crippling of economies globally. The effects are substantial on health, economy, environment, and society. Nearly every country is trying to prevent the transmission of this communicable disease. Remedial policies include testing and treating patients, isolating suspects through contact tracking, banning public gatherings, and asserting a complete or partial shutdown. In this context, the present paper's core objective is to investigate the impact of the COVID-19 pandemic on the environment and energy market, society, economy, and global protective measures taken to reduce COVID-19 transmission. The study's main contribution is revealed lessons to provide insights for business and the efficacy of governments’ initiative globally. Finally, this paper describes future actions for governments, leaders, energy providers, and all stakeholders in response to the global pandemic crisis.

The agri-food sector is an endless source of expansion for nourishing a vast population, but there is a considerable need to develop high-standard procedures through intelligent and innovative technologies, such as artificial intelligence (AI) and big data. This paper addresses the research concerning AI and big data analytics in the food industry, including machine learning, artificial neural networks (ANNs), and various algorithms. Logistics, supply chain, marketing, and production patterns are covered along with food sub-sector applications for artificial intelligence techniques. It is found that utilization of AI techniques and the intelligent optimization algorithm also leads to significant process and production management. Thus, digital technologies are a boon for the food industry, where AI and big data have enabled us to achieve optimum results in realtime.

Purpose: The purpose of this paper is to identify the non-value-adding activities (NVAs) of core making process and to eliminate them through the standardization-of-work (SW) procedures in a manufacturing company. Design/methodology/approach: The action-research methodology was adopted for the current study. First, various lean tools were identified through literature review, and the bottleneck area was identified in discussion with the shop-floor executives. NVAs were recorded after a continuous process study including method study and motion analysis followed by the standard operating procedure. Second, the standardized work combination tables were prepared and NVAs were eliminated using the SW procedures. SW has been opted because it is a set of actions which helps in analyzing, improving and controlling the process and it leads to continual improvement. Findings: The production logbook revealed that the capacity in this particular workstation was 54 pieces per 7 h work shift against the current production of approx. 45–50 pieces (past data). SW saved 31.6 s per cycle which boosted the production up to 58 pieces per 7 h work shift. Finally, the authors came to know that the productivity of this particular process increased up to 6.5 percent which may upsurge if this action is executed continually with the support from shop-floor executives and management. These results were also compared with previous research works in this area and found significant relevance, and hence, the results appear to be reliable. Research limitations/implications: This is a unique study in itself which explores the lean model by assessing NVAs of core making process. The proposed approach needs to be tested across different other core making processes of the case company so as to generalize the effectiveness of SW as well as the results obtained in the current study. Practical implications: The current study illustrates an important step to give more visibility to the lean concept by addressing the problem of lack of standard procedures. This study will help the shop-floor executives and managers to focus their efforts in achieving high performance through effective implementation of SW. The study should be of the interest of researchers in the area of lean manufacturing, operations management, productivity analysis, etc. Originality/value: The findings of this study are based on the problem formulation for productivity gains using SW procedures in the case company. The study introduces a new perspective for the execution of SW for core making processes. SW created transparency in workflow, enhanced the safety and eliminated the 3Ms. The outcome of the current study was discussed with the production team and management of the company to validate the productivity gains and received an optimistic response. Most importantly, these improvements were achieved with no investment in machinery or tooling.