Opportunities for the digital transformation of the banana sector supply chain based on software with artificial intelligence

Artificial intelligence offers great opportunities for the supply chain, being this a competitive advantage for today’s changing market. This article aims to identify the impacts and opportunities that artificial intelligence software can offer to facilitate the operation and improve the performance of the supply chain in the banana sector in Colombia. The work methodology consists of six steps in which a total of 72 investigations were obtained. The sources of information were four databases. As a main conclusion, the supply chain of the banana sector has everything necessary for intelligent software based solutions to be implemented in order to achieve adaptation, flexibility and sensitivity to the context and domain of execution

A Literature Review on The Design of Intelligent Supply Chain for Natural Fibre Agroindustry

Natural fibre is an environmentally friendly raw material that has a great potential to develop, and is abundantly available in nature [1]. Currently, the growth of natural fibre processing industries in the world has been increasingly important [2]. Processing of abundant natural fibre in both upstream and downstream productions requires effective and collaborative supply chain management in terms of information sharing. Thus, an intelligent system would be implemented in supply chain management from upstream to downstream. Based on review of 46 scientific papers discussing on types of natural fibre, process, technology, and methods, as well as application areas of natural fibre in downstream industries. According to review on different aspects in 55 scientific papers, there were 5 aspects mapped, i.e. supply chain analytic, value chain, performance, collaboration, big data, and decision support system. A concept of 4.0 industry underlies utilization of opportunities for application of supply chain analytic [3]. Upcoming research opportunities include mediating relationship in supply chain network by utilizing Internet of things (IoT) and Big data (BD), in a collaborative relationship to use information sharing. The most possibly contributing research is the development of collaboration between supply chain and genetic algorithm [4]. Integration between production and inventory planning becomes an approach that utilizes Particle swarm optimization (PSO) by developing production planning [5], and production and inventory planning [6]. There is a research opportunity in the design of intelligent supply chain for natural fibre agroindustry by implementing IoT and BD as a tool in supply chain analytic, collaboration through Collaboration prediction forecasting and replenishment (CPFR) that occurs between stakeholders with the aim of improving agroindustry supply chain performance in production integration material and inventory, and performance measurement by integrating the Value chain operation reference (VCOR) model developed in supply chain analytic

Multi-objective optimization for preemptive & predictive supply chain operation

At present, the manufacturing industry has undergone a tremendous change in its operating principle with respect to the supply chain management system where the demands of consumers are dynamically and exponentially rising. Although Industry 4.0 offers a significant solution to this principle with the aid of its predictive automated operating process, till date there is less number of fault tolerant model that can effectively meet the standard demands of supply chain planning. Therefore, the proposed system introduces an analytical model where predictive optimization is carried out towards bridging the gap between supply and demands in supply chain 4.0. An analytical framework is a design from constraints derived from practical environment in order to offer better applicability of it. The study outcome shows that the proposed model could offer better performance in comparison to the existing optimization method with respect to the better budget control system for offering predictive and preemptive model design

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain.La inteligencia artificial ofrece grandes oportunidades para la cadena de suministro, siendo esto una ventaja competitiva para el mercado cambiante de hoy en día. Este artículo tiene como objetivo identificar los impactos y oportunidades que puede ofrecer el software con inteligencia artificial para facilitar la operación y mejorar el desempeño de la cadena de suministro en el sector bananero de Colombia. La metodología de trabajo consta de seis pasos en donde se obtuvo un total de 72 investigaciones. Las fuentes de información fueron cuatro bases de datos. Como conclusión principal, la cadena de suministro del sector bananero tiene todo lo necesario para que se implementen soluciones basadas en software inteligente con el fin de lograr una adaptación, flexibilidad y sensibilidad al contexto y dominio de ejecución.   Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain

Achieving resilience in the supply chain by applying IoT technology

In the past few decades, competition has increased between organizations as a result of globalization and fast development in IT. Companies these days are continuously looking to expand their market geographically to attract new customers. With that in mind, the main concern of companies is to achieve their customers’ requirements, which makes the supply chain (SC) longer and more complex. This leads to increased difficulty in managing the SC along with controlling risks and disruptions in SC. Such as loss of a critical supplier, a fire accident in the production facility, or an act of terrorism. To deal with these risks, SC must be designed to provide an efficient and effective response, keep its process working and be capable of recovering to their original state after disruptive events, this is considered as the core of supply chain resilience (SCRes). Furthermore, companies that design their SC with capabilities to react quickly to any disruptions in its process have the opportunity to become more stabilized and acquire an improved position in the market. Researchers have been exploring ways to acquire supply chain resilience, such as encouraging and improving collaboration between SC partners or by increasing the organization’s visibility through monitoring SC events and patterns. Studies have shown that IT has a role in improving SCRes, such as information-sharing systems to promote collaboration and visibility tactics. However, recent research trends are exploring new and emerging technologies like the Internet of Things (IoT). Despite the growing interest in IoT, minimal research has been carried out for its application in SCRes. Research in this direction is necessary to explore opportunities provided by IoT to redesign SC which in turn reinforces flexibility of supply chains and aspects of analysis of the product quality and how it could enable companies to improve their SCRes. This study is directly focused to identify and highlight this gap.N/

A systematic literature review on machine learning applications for sustainable agriculture supply chain performance

Agriculture plays an important role in sustaining all human activities. Major challenges such as overpopulation, competition for resources poses a threat to the food security of the planet. In order to tackle the ever-increasing complex problems in agricultural production systems, advancements in smart farming and precision agriculture offers important tools to address agricultural sustainability challenges. Data analytics hold the key to ensure future food security, food safety, and ecological sustainability. Disruptive information and communication technologies such as machine learning, big data analytics, cloud computing, and blockchain can address several problems such as productivity and yield improvement, water conservation, ensuring soil and plant health, and enhance environmental stewardship. The current study presents a systematic review of machine learning (ML) applications in agricultural supply chains (ASCs). Ninety three research papers were reviewed based on the applications of different ML algorithms in different phases of the ASCs. The study highlights how ASCs can benefit from ML techniques and lead to ASC sustainability. Based on the study findings an ML applications framework for sustainable ASC is proposed. The framework identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability

Application of Optimization in Production, Logistics, Inventory, Supply Chain Management and Block Chain

The evolution of industrial development since the 18th century is now experiencing the fourth industrial revolution. The effect of the development has propagated into almost every sector of the industry. From inventory to the circular economy, the effectiveness of technology has been fruitful for industry. The recent trends in research, with new ideas and methodologies, are included in this book. Several new ideas and business strategies are developed in the area of the supply chain management, logistics, optimization, and forecasting for the improvement of the economy of the society and the environment. The proposed technologies and ideas are either novel or help modify several other new ideas. Different real life problems with different dimensions are discussed in the book so that readers may connect with the recent issues in society and industry. The collection of the articles provides a glimpse into the new research trends in technology, business, and the environment

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development