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In the context of great changes in the food industry, the aim of this research is to investigate if and how the implementation of 4.0 enabling technologies can enhance the economic, environmental and social sustainability of the food sector. A systematic literature review, using a combination of 12 keywords, was carried out on Scopus database with defined inclusion and exclusion criteria in order to answer four selected research questions. Overall, 50 relevant papers were retrieved and analysed by Mendeley and Excel with descriptive statistics. VOSviewer was used for co-occurrence and co-authorship analysis. Results illustrate that the interest in the topic has grown, in particular in Italy, and resume the benefits achievable by the implementation of 4.0 technologies in food industries. Social impacts are new job positions, ergonomic design of workplaces, changes in educational institutions, improved nutrition and better animal welfare. Positive aspects are related even to economic growth, improving food chain performances and decreasing companies' costs. Finally, it allows energy, water, CO2 emissions and food savings. Overall, the work provides a helpful overview to food manufacturers and producers, recommending the introduction of I4.0 technologies to positively influence the sustainable development of the sector and remain competitive in the market. [ABSTRACT FROM AUTHOR]

The competition among Food & Beverage companies has substantially increased in today's age of digitization. Sales forecasting is one of their main challenges. Due to space limitations, employee shortages, and rising online demand, retail sales forecasting became extremely important for Food and Beverage companies. This research analyzed the sales data of a multinational Food & Beverage Company. It proposed a framework using Gaussian Mixture Model (GMM) clustering, Hierarchical Agglomerative Clustering (HAC), and Random Forest algorithm for forecasting sales. This model analyzes the impact of the weekends, holidays, promotional activities, customer sentiments, festivals, and socio-economic situations in sales data and is able to forecast sales ranging from one to 15 months. An investigation of the suggested model's performance compared to numerous cutting-edge sales forecasting techniques is carried out to show its efficacy. Here, we demonstrate that the proposed hybrid model surpasses current predicting and computing efficiency methods. The results of this study can help retail managers to allocate resources and manage inventories in well-informed ways. The findings suggest that combining many strategies may produce the most precise forecasts. [ABSTRACT FROM AUTHOR]

Nowadays many processes in the food industry are monitored in an automatic way, with the purpose of minimising the need for workforce and of ensuring the proper control of the quality and safety of the foodstuff. All the sensors share data with a centralised management unit, where often a Manufacturing Execution System collects and evaluates them. As reported in recent research, however, a further step that can be undertaken, exploiting Industry 4.0 enabling technologies, is the implementation of digital twin approaches, with the additional aim to prevent possible issues during production. In line with these considerations, this work aims at showing two different digital twin models intended for improving the control of as many real food systems. Liquid and powder fluids are taken as examples for highlighting the differences in the optimization of the two food processes, as well as for fully exploring the potential of the digital twin approach. Finally, based on the real data taken from two pilot plants, a framework for the selection of the best digital twin tool in the food sector is delineated. [ABSTRACT FROM AUTHOR]

In recent years, the emerging Digital Twin (DT) paradigm under Industry 4.0 has been attracting more attention from both practitioners and academia due to its dynamic capabilities. Most DT studies are theoretical and deal with hypothetical analysis, whereas fewer studies are available on real-life empirical cases. Due to dynamic problem-solving capabilities, DT technologies are widely used in performance improvement analysis in food processing companies (FPC) despite limited implication's for business strategies. Our study incorporates the DT technologies with an implementation case study on FPC and accomplishes the real-life problem of the food processing company (FPC). Moreover, the proposed DT research framework demonstrates the various DT implementation stages, such as strategic mapping and physical-virtual space replica, with rigorous analysis. The results show that DT enhances the existing system's machine availability, allocation efficiency, technical efficiency, worker efficiency, utilization rate, effectiveness, step ratio, and throughput rate. The proposed physical-virtual interface model is executed using AnyLogic software with JAVA-enabled programming. [ABSTRACT FROM AUTHOR]

We consider a real-world scheduling problem arising in the colour printing industry. The problem consists in assigning print jobs to a heterogeneous set of flexographic printer machines and finding a processing sequence for the jobs assigned to each machine. The machines are characterised by a limited sequence of colour groups and can equip additional components (e.g. embossing rollers and perforating rolls) to process jobs that require specific treatments. The process to equip a machine with an additional component or to clean a colour group takes a long time, with the effect of significantly raising the setup times. The aim is to minimise a weighted sum of total weighted tardiness and total setup time. The problem derives from the activities of an Italian food packaging company. To solve it, we developed a greedy randomised adaptive search procedure equipped with several local search procedures. The excellent performance of the algorithm is proved by extensive computational experiments on real-world instances, for which it produced good-quality solutions within a limited computing time. The algorithm is currently in use at the company to support their weekly scheduling decisions. [ABSTRACT FROM AUTHOR]

We study a problem from a real-world application, in which a daily set of orders must be processed following two stages, consisting of preparing perishable products on benches and allocating them to conveyors to be packed in disposable trays. Daily decisions must be made regarding the number and start time of working shifts, the number of workers and their allocation to machines, and the scheduling of orders in a two-stage flexible flow shop environment. The flow shop environment of the studied problem is common in many industries of perishable products, making the problem very general. The problem involves a number of operational constraints, and three objective functions that are minimised in a lexicographic way. To solve the problem, we implement a constructive heuristic and embed it within three metaheuristics: a Random multi-start algorithm (MR), a Biased random key genetic algorithm (BRKGA), and a Variable neighbourhood search (VNS) based one. We perform computational experiments over a set of realistic instances, and present a lower bound obtained from a constraint programming model for the scheduling counterpart. The results of the experiments show that the BRKGA is the most effective in practice for the integrated problem of workforce allocation and scheduling. [ABSTRACT FROM AUTHOR]

BackgroundAs the only place in a store where customers must pass through, checkouts may be especially influential over purchases. Research is needed to understand the healthfulness of checkout environments.ObjectivesThe objective of this study was to classify checkout product facings in California food stores.MethodsIn a cross-sectional study, 102 stores, including chains (dollar stores, drugstores, specialty food stores, supermarkets, and mass merchandisers) and independent supermarkets and grocery stores were sampled from 4 northern California cities. Observational assessments of each checkout product facing were conducted in February 2021 using the Store CheckOUt Tool. Facings were classified by category and healthfulness, defined by meeting Berkeley's Healthy Checkout Ordinance's healthy checkout standards: unsweetened beverages and specific foods containing ≤5 g added sugar and ≤200 mg sodium per serving. Log binomial regressions compared healthfulness by store and checkout characteristics.ResultsOf 26,758 food and beverage checkout facings, the most common categories were candy (31%), gum (18%), sugar-sweetened beverages (SSBs; 11%), salty snacks (9%), mints (7%), and sweets (6%). Water represented only 3% and fruits and vegetables 1% of these facings. Only 30% of food and beverage facings met Berkeley's healthy checkout standards, with 70% not meeting the standards. The percentage of food and beverage facings not meeting the standards was even higher (89%) among snack-sized packages (≤2 servings/package). Compared with chain supermarkets, mass merchandisers, and specialty food stores (34%-36%), dollar and independent grocery stores had a lower percentage of food and beverage facings that met the healthy checkout standards (18%-20%; P < 0.05). Compared with lane and register areas (35%), endcaps and snaking sections within checkouts had fewer food and beverage facings that met the standards (21%-23%; P < 0.001).ConclusionsMost foods and beverages at checkout consisted of candy, SSBs, salty snacks, and sweets and failed to meet the healthy checkout standards.Curr Dev Nutr 2023;xx:xx.

Plant polyphenols are a class of plant secondary metabolites containing several phenolic hydroxyl groups in their molecular structure, which have physiological properties such as anti-inflammatory, anticancer, antibacterial, etc., and can be used as excellent dietary supplements. However, some of the polyphenols are poorly stabilized, and they are prone to degradation during food production, processing, and storage, so it is necessary to use encapsulation technology to improve their stability and maintain their activity at the same time. The emulsion possesses the characteristics of stability and versatility with the potential to encapsulate and protect plant polyphenols. This paper firstly analyzes the properties of plant polyphenols and the underlying reasons for their limited applications, further discusses the encapsulation effect of different types of emulsions (normal emulsion, microemulsion, nanoemulsion, Pickering emulsion, multilayer emulsion and emulsion gel, etc.) on polyphenols, and finally summarizes the current status of polyphenol emulsion encapsulation systems in the food industry such as meat, fruits and vegetables, ice cream, bakery, and beverage, etc., and provides an overview of polyphenol emulsions in the future preparation direction and its development direction in the food field. This paper can provide some reference for the application of plant polyphenol emulsion encapsulation system in the future food industry.

The food industry is currently demonstrating a tendency to substitute traditional high-humidity raw materials with their dry analogues. This research introduces new designs of vertical vibrating mixers that could preprogram flour mix quality. The vertical continuous vibration mixers designed for granular materials showed a good potential for a wider scope of application. The experiment involved high-quality wheat flour, sugar, salt, egg powder, and powdered milk, as well as three vertical mixers, i.e., a lifting mixer, a flow mixer, and a cascade mixer. Wheat flour entered the working body of the mixer and came into a stable vibration-boiling state in layers of ≤ 35 mm with a vibration amplitude of 4.5 mm and a frequency of ≥ 20 Hz. The speed rate of the flour increased together with the oscillation frequency of the working body and the size of the perforation area but went down as the layer grew wider. The efficiency increased following the increase in the perforation area on the spiral surface and depended on the maximal thickness of the dough layer. The flow vibrating mixer proved to be the most effective one. The frequency of pulse feeding of ingredients into the mixer was ≤ 50% (Vc ≤ 14.5%) to obtain flour mixes of satisfactory quality while good-quality mixes required 25% average time the particles spent in the mixer (Vc ≤ 6%). The results obtained can be used to design technological lines for flour mix production.

Ultraviolet (UV) irradiation is a non-thermal sterilization technique, and mercury vapor ultraviolet lamps currently serve as the primary equipment for food hygiene. However, due to some factors, the production and usage of mercury lamps gradually reduced. The inevitable trend has been their replacement by environmentally friendly and energy-efficient ultraviolet light-emitting diodes (UV-LED). This article, based on the principles of UV-LED light emission and the characteristics of multi-wavelength coupling applications, briefly reviewed the mechanisms of microbial inactivation. The factors affecting the inactivation effect (wavelength, UV dose and material characteristics), the sterilization effect of processed foods and the impact on the quality of some foods were explored. The aim was to provide a reference for optimizing the sterilization processes and equipment parameters of UV-LED in the field of food hygiene.

This literature review explores of Analytical Hierarchical Process (AHP) application in conjunction with Intuitionistic Fuzzy Sets (IFS) as a powerful decision-making framework within the context of the food manufacturing industry. The review synthesizes a wide array of research contributions and findings to provide insights into the dynamic and uncertain nature of this industry. The study reveals that the AHP-IFS methodology offers a structured approach to address the complexities inherent in the food manufacturing sector, which undergoes distinct phases from inception to maturity, and potentially, decline or renewal. Decision criteria and factors, including market dynamics, technological advancements, regulatory compliance, sustainability concerns, and financial considerations, are analyzed and prioritized using AHP-IFS, considering their interdependencies and uncertainties. Strategic planning, resource allocation, and competitive analysis within the industry have been significantly enhanced through the application of this methodology. Moreover, as sustainability and environmental issues become increasingly important, AHP-IFS is also employed to evaluate the environmental impact of business decisions, aligning with global efforts to promote sustainability. Challenges associated with data availability and computational complexities have been acknowledged, but the potential for refinement and expansion of the methodology, including the incorporation of machine learning techniques, offers promising avenues for future research. Ultimately, AHP-IFS stands as a valuable tool to guide informed decision-making processes throughout the ever-evolving business life cycle of the food manufacturing industry, ensuring adaptability and competitiveness in a complex and uncertain landscape.