Product Delivery Research Articles

Do artificial intelligence system adoptions foster production management supply chain performance in pharmaceutical manufacturing firms? An empirical exploring study from the MENA region

PurposeThe goal of this study is to better understand the driving force behind the use of artificial intelligence (AI) in pharmaceutical manufacturing firms (PMFs) that are recognized as developing countries in the Middle East and North Africa (MENA) region that are listed by the Chambers of the Industries of Jordan, the Kingdom of Saudi Arabia, Morocco, and Algeria. Furthermore, the effect of adopting and using AI in managing raw materials (RMs), products, parts, and components for PMFs through supply chains (SCs).Design/methodology/approachA self-administrated questionnaire survey was used to gather data from 95 out of 511 participating managers (e.g. manufacturing, supplying, IT, operational, and logistical managers) utilizing a quantitative technique with a random sample size. In fact, 18.8% of the 89 different manufacturing firms (MFs) in the MENA area responded, with five to six managers from each company. The raw data was analyzed using partial least squares structural equation modeling (PLS-SEM).FindingsThe study’s findings show that the readiness to embrace artificial intelligence (AI) in the production management supply chain performance (PMSCP) of pharmaceutical manufacturing firms in the Middle East and North Africa (MENA) is positively and significantly influenced directly and indirectly by sustainable strategic supplier reliability (SSSR), shipping process dependability (SPD), technological factors (TFs), and infrastructure transformational development capability (ITDC).Originality/valueAs the studied countries are growing economies, such study findings might offer insightful consequences for stakeholders and policymakers regarding the significance of using artificial intelligence system adoptions in pharmaceutical manufacturing enterprises in the MENA region. The managers may also concentrate on the strong positive direct and indirect links between SSSR, SPD, TFs, and ITDC preparedness to accept AI adoption and its applications and systems in supply chain and production management departments and the consequences of informational and product delivery.

Analisis dan Pemodelan Proses Bisnis Katering pada UMKM Menggunakan BPMN

Fafiras Kitchen is a family business that focuses on food catering services. This business involves three main operational stages, namely the ordering process, procurement of raw materials, and delivery of products to customers. From the results of observations and interviews, several problems were identified such as the absence of good records in the ordering process resulting in errors in order fulfillment and loss of customer data, dependence on one raw material supplier increases the risk of delays and disruptions in the supply chain and inefficient delivery management caused by human error and no real time tracking, so this has an impact on customer loyalty. This research aims to analyze and model the current business process and provide recommendations for improvement. Modeling is done using Business Process Model and Notation (BPMN) with a qualitative approach to investigate existing business processes. The results of this research can identify areas of improvement to increase the efficiency and effectiveness of MSMEs operations so that MSMEs can better understand, manage, and optimize their business processes. In addition, this research also conducted simulations using the Bizagi Modeler application to test the validity of the business process modeling that has been made. The simulation results show an increase in time in the implementation of business processes.

Sistem Informasi Manajemen E-Budidaya CV.Tarkiz Paz Banua

The development of information technology has had a significant impact on various sectors,including animal husbandry. Livestock sustainability requires effective and inexpensive solutions.This research was born in response to a request from livestock sector operators to the softwarehouse company CV.Tarkiz Paz Banua to develop an E-Budidaya management information system.The aim of the close collaboration between software companies and livestock sector operators isto increase the affordability of livestock operations, with a focus on providing food and medicineto livestock. This research involves designing and developing an E-Budidaya management systemthat facilitates product sales, and ensures quick access to product information. By utilizing digitaltechnology, it is hoped that the ordering, payment and product delivery processes can be carriedout efficiently, thereby increasing customer satisfaction and strengthening business relationshipsbetween partners and operators in the livestock sector. The E-Budidaya management informationmanagement system also provides the latest information on livestock products, includinginstructions for use, nutritional composition and dosage recommendations, thereby increasingagricultural knowledge and providing added value to the company's products. This study reflectsthe contribution of positive collaborative innovation between software companies and livestock companies through effective digital solutions that improve operational efficiency, customerservice and product added value in narrow markets.

Guyana’s Ongoing Commitment to Food Safety: Protecting Public Health Everyday

Guyana is better equipped to adapt to the evolving challenges and complexities of the food supply chain while ensuring the consistent delivery of safe and quality food products to its citizens.

ORGANIZATION OF DELIVERY OF THE COMPANY'S PRODUCTS BY OWN VEHICLES

Purpose. The purpose of the work is the formation and analysis of options for the organization of the delivery of the machine-building enterprise's products by its own vehicles. Methodology. The main stages of choosing a rational technology for the organization of product transportation by own transport based on the developed schedules have been formed. The research was performed on the basis of the analysis of graphs of the dependence of motor vehicle operation indicators on the technology of organizing the transportation of the company's products. Findings. The article develops and analyzes work schedules for the delivery of the company's products by tractor-trailer trucks with semi-trailers. According to the schedules, the duration of delivery of one product in a ready-to-install condition to the consignee, the maximum possible annual volumes of transportation, the maximum and actual average annual operating costs for the delivery of the company's products by its own vehicles are determined. Practical value. The results of the research can be used to make a decision on the expediency of refusing the services of logistics companies to organize the delivery of the company's products to customers.

A location-production-routing problem for distributed manufacturing platforms: A neural genetic algorithm solution methodology

Additive Manufacturing (AM) enhances the flexibility of manufacturing networks. In this paper, we present a Location-Production-Routing (LPR) problem designed for a distributed manufacturing platform, where the manufacturing facilities are distributed in different locations with the support of AM technologies. The proposed LPR problem encompasses three different types of decisions: location-allocation, production planning, and product delivery routing decisions. This is one of the first studies that analyzes integrated logistics and manufacturing optimization under distributed and resilient manufacturing platforms. To efficiently solve the complex problem, we design a novel solution method called the Neural Genetic Algorithm (NGA). The numerical experiments show that the proposed method can attain near-optimal solutions, achieving an average gap of 3% with a standard deviation of 1.4% and a 99% improvement in computational time compared to the CPLEX solver. The sensitivity analysis illustrates the high impact of the unit shortage cost on the customer service level and on the distribution of the AM facilities. Moreover, our results for a given instance show that through the periodic reconfiguration of AM supply chains using the proposed LPR model, we can achieve an average cost reduction of up to 25% in the supply network.

A novel fuzzy finite-horizon economic lot and delivery scheduling model with sequence-dependent setups

This paper addresses the economic lot and delivery scheduling problem (ELDSP) within three-echelon supply chains, focusing on the complexities of demand uncertainty, limited shelf-life of products, and sequence-dependency of setups. We develop a novel mixed-integer non-linear programming (MINLP) model for a supply chain comprising one supplier, multiple manufacturers with flexible flow shop (FFS) production systems, and multiple retailers, all operating over a finite planning horizon. The common cycle (CC) strategy is adopted as the synchronization policy. Our model employs fuzzy set theory, particularly the “Me measure,” to effectively handle the retailers’ demand uncertainty. Our findings indicate that total supply chain costs escalate with an increase in demand, final components’ holding costs, and sequence-dependent setup costs, but decrease with increasing production rates. Furthermore, while total costs are significantly sensitive to changes in demand, they are relatively insensitive to fluctuations in sequence-dependent setup times. The models developed offer valuable managerial insights for optimizing costs in synchronized multi-stage supply chains, aiding managers in making informed decisions about production lot sizes and delivery schedules under both deterministic and fuzzy demand scenarios. Additionally, the proposed models bridge key research gaps and provide robust decision-making tools for cost optimization, enhancing supply chain synchronization in practical settings.

A distributionally robust optimization approach for the potassium fertilizer product transportation considering transshipment through crossdocks

Potassium fertilizer is an essential input for agricultural productivity, and plays a critical role in various plant processes, influencing water uptake, enzyme activation, and photosynthesis. The efficient delivery of potassium fertilizer products to the end-users, typically farmers and agricultural enterprises, is of utmost importance. Due to the long traveling distance between the supplier and customers, decision makers of supplier normally set up multiple crossdocks to aid in transition and storage of potassium fertilizer products. In this situation, making an optimal transportation plan as well as the inventory level of crossdocks will directly enhance the efficiency and effectiveness of long-distance transportation. In this study, we model this problem as a dynamic transportation problem with transshipment considering the uncertain time-varying customers’ demand. To characterize the demand information, we first construct an ambiguity set of customers’ demand based in limited historical data and then develop a distributionally robust optimization-based (DRO) framework to optimize the transportation plan and related inventory level of crossdocks simultaneously. We also propose a general approach to overcome the computational challenges of DRO by transforming the original DRO into a second-order cone programming based on duality theory. Additionally, we introduce linear decision rules to adjust the optimization strategy based on the new observed demand, thus lead the model to handle the dynamic information flow in real time. In case study, all involved data are collected or derived from a real potassium fertilizer company located at Western China. The results show our model reduces the cost by 18.07% compared to stochastic model (sample average approximation), indicating a significant effectiveness of our model on the improvement of delivery efficiency and cost saving in real dynamic logistic systems. Also, we conclude the managerial insight that decision-makers should develop a comprehensive strategy, including improving communication to ensure order status updates, planning rationally to evenly distribute orders, and proactively allocating resources to meet operational demands.

Implementation of a Technical Peer Review Process: Principles, Policy, and Cultural Change

AbstractThe complex scientific and engineering work performed at Sandia National Laboratories is supported by a comprehensive system of reviews that include design, gate, and peer reviews. A recent exercise revealed a need to change how technical peer reviews are conducted. Building on industry standards, best practices, current standard internal practices and other previous work, Sandia has developed a continuous improvement process to institutionalize technical peer review in the design lifecycle of products. The approach focuses on translating customer and leadership expectations, utilizing current established practices, simplifying planning and execution, and providing resources to project teams to guide them and ensure that rigorous and consistent technical peer reviews are performed. This paper presents the process used by Sandia to improve the technical peer review process, the factors that affect implementation of a peer review process, the simplified three‐step process implemented, the tools and resources generated, and the sustainment plan adopted to increase the institution‐wide use of peer review as a tool to improve product delivery.

Branch-Price-and-Cut algorithms for the team orienteering problem with interval-varying profits

This paper studies the team orienteering problem (TOP), wherein each vertex requires two visits, and the service profit of each vertex depends on the time interval between these two visits. Motivated by scenarios like perishable product delivery, home health care scheduling, and earth observation satellite scheduling, the paper addresses two variants: the periodic orienteering problem with a focus on the number of days (NoDs) and the team orienteering problem with attention to a combination of time windows (CoTWs). It develops mixed-integer linear programming (MILP) models for both variants and devises exact Branch-Price-and-Cut (BPC) algorithms tailored to their block diagonal structures. Furthermore, this paper proposes two strategies to improve algorithm performance. A simplification strategy streamlines the directed graph network by removing redundant vertices and arcs without compromising optimality, thereby accelerating the solution of pricing problems. Additionally, a matheuristic algorithm is proposed to obtain integer solutions quickly. Computational results demonstrate the effectiveness of these algorithms, showcasing their superiority over CPLEX. The BPC algorithm, coupled with the simplification strategy, exhibits an average computational time reduction of 70 % compared to the basic strategy. The effectiveness of the matheuristic algorithm is also confirmed. Finally, the findings presented herein offer valuable insights for refining and applying BPC algorithms.

Livestock Value Chain Mapping in Kajiado and Narok Counties, Kenya

The livestock value chain encompasses a comprehensive range of activities involving various actors that facilitate the conveyance of the final product to the consumer through different stages of collection, processing, production, and final delivery. This case report presents the findings from the mapping of livestock value chains in Narok and Kajiado Counties, Kenya. The study aimed to determine the status and gaps within the value chain, as well as the technological needs of enterprises engaged in the value chain. The ultimate goal was to foster innovation, enhance the productivity of Small and Medium Enterprises (SMEs), improve managerial and technical skills, strengthen local supply chains, and reduce gender disparities within the value chain. The study employed well-structured questionnaires and interviews in both counties to capture the technological status and needs, map all stages of the value chains, outline the main activities and actors, and identify existing gaps. Three primary value chains in the livestock subsector were identified: dairy, beef, and leather. Each of these value chains was studied and analyzed separately. The activities and actors involved at each stage, from inputs and production to transformation and marketing, were examined. The findings highlight intervention areas and provide recommendations to improve the three value chains.

E-Commerce Information System Design Using SpringBoot Framework and PostgreSQL

Advances in information technology, especially in the field of information technology, have become an integral part of our daily lives. The increasing volume and complexity of data affects almost all aspects of our activities, including education, sales, transportation, banking, and others. In a world filled with advanced technology, people expect speed and convenience in everything. Therefore, businesses need to design and build effective and reliable e-commerce information systems to meet the demands of an increasingly connected and digitalized market. In this research, e-commerce information systems are faced with the demand to efficiently manage various aspects of business such as product management, stock, transactions, delivery, and payment. RESTful web services are used as a solution to facilitate data exchange between various systems effectively by using SpringBoot Framework, which is chosen as an easily configurable and efficient framework. In addition, security and flexibility in data management were in focus, with PostgreSQL chosen as a database capable of dealing with large data volumes and providing a good level of security. By combining SpringBoot-based RESTful web services and the use of PostgreSQL database, the e-commerce information system can provide high performance, integrated, and secure, improving the user's shopping experience and building customer trust in the e-commerce platform used. The research method used by researchers in the design of this information system is the System Development Life Cycle (SDLC) which includes planning, analysis, design and implementation.

Entrega de produtos em áreas urbanas utilizando drones: análise de direito comparado da legislação regulatória aeronáutica

The aim of this paper is to analyze the possibility of using regulatory solutions applied in another country to help improving Brazilian aeronautical legislation regarding the use of drones for the delivery of products and food at home. In addition to its military origin, the article brings the definitions of drones, their classes, as well as the types of flight of this equipment. The current scenario of e-commerce and home food delivery in Brazil is presented below, with emphasis on its abrupt growth during the COVID-19 pandemic. Next, we present and analyze the US legislation that defines the process for using drones to deliver products and to obtain the drone pilot certificate and the subsequent comparison between the legal systems. Finally, the article concludes on the urgent need to improve Brazilian legislation to allow the use of drones to deliver products in urban areas, taking advantage of US solutions as a starting point. From a documentary and bibliographic research, the article uses deductive and comparative methods.

Pengoptimalan Persediaan Bahan Baku Utama Untuk Mengatasi Tantangan Industri Menggunakan Metode Just In Time (JIT) Dan Silver Meal Heuristic Pada PT. Indonesia Plafon Semesta

The inventory problem that still occurs at PT Indonesia Plafon Semesta is the accumulation of resin and calcium raw materials which results in considerable losses. PT Indofon began to experience a buildup of resin raw materials in August amounting to 16,100Kg and for calcium amounting to 15,200Kg so that each month it soared until its peak in October, namely a buildup of 23,500Kg of resin, and 23,200Kg of calcium. The use of the right method for inventory control problems is Just In Time , which is a management strategy used to optimize the production process and product delivery by buying and producing only when needed and at the right time. Silver Meal Heuristic, a heuristic approach used in inventory control to determine the optimal lot size. The quantity of raw material orders using JIT is relatively more than the silver meal, but with JIT the supplier only needs to send 4-5 times, meaning that the company can save costs. The quantity and frequency obtained from data processing using silver meal is more optimal. However, the cost of raw material inventory incurred is quite large. For a decrease in efficiency costs by implementing a policy of making purchases with Just In Time (JIT) and is expected to save on raw material inventory costs. So that these cost savings can be allocated by the company to other costs.

Improved SVM-LSTM-based resource flow forecasting for the low-carbon urban distribution grid

Resource flow supports the delivery of products and services and plays a vital role in the low-carbon urban distribution grid. Therefore, reasonable forecasting of the resource flow is essential for financial decision-making. Through the trained model, the resource flow forecasting process can be simplified and one-click forecasting can be realized. However, this method relies on the selection and optimization of model parameters, where poor parameter choices can significantly impact the forecasting accuracy. This paper first introduces a model for identifying key influencing factors in resource flow data, incorporating an elastic network and gray correlation analysis. Subsequently, a resource flow forecasting method based on improved support vector machines–long- and short term memory (SVM-LSTM) is proposed. Finally, the superior performance of the proposed method is validated through simulations.

How can hotels Co-create value through the localized mini bar in the room: discrete choice modeling approach with CSR strategies with local products

ABSTRACT Even though Hotel mini bars is an excellent service and product delivery channel during the guest stay, typical selections of varieties and displays have been used without innovative ideas. This study argues that Mini Bars in the hotel can be capitalized to share the Hotel’s Corporate Social Responsibility vision and enhance customer perception toward the hotel brands with revenue increase. The current study adopts Discrete Choice Modeling to investigate the best choice attributes and levels of hotel mini bar. The results address how the hotel and local industry can co-create value for the hotel, local businesses, and guests.

Gelatin methacryloyl microneedle loaded with 3D-MSC-Exosomes for the protection of ischemia-reperfusion

Exosomes (Exo) generated from mesenchymal stem cells (MSCs) have great therapeutic potential in ischemia-reperfusion treatment. For best therapeutic effect, high quality Exo product and effective delivery system are indispensable. In this study, we developed a new strategy for ischemia-reperfusion recovery by combining MSCs 3D (3D-MSC) culturing technology to generate Exo (3D-MSC-Exo) and microneedle for topical delivery. Firstly, primary MSCs from neonatal mice were isolated and 3D cultured with gelatin methacryloyl (GelMA) hydrogel to prepare 3D-MSC-Exo. The 3D-MSC showed better viability and 3D-MSC-Exo exhibited more effective effects of reducing neuroinflammation, inhibiting glial scarring, and promoting angiogenesis. Subsequently, the biocompatible GelMA was used to construct microneedles for 3D-Exo delivery (GelMA-MN@3D-Exo). The results demonstrated GelMA microneedles had excellent 3D-Exo loading capacity and enabled continuous 3D-Exo release to maintain effective therapeutic concentrations. Furthermore, the rat middle cerebral artery occlusion (MCAO) model was established to evaluate the therapeutic effect of GelMA-MN@3D-Exo in ischemia-reperfusion in vivo. Animal experiments showed that the GelMA-MN@3D-Exo system could effectively reduce the local neuroinflammatory reaction, promote angiogenesis and minimize glial scar proliferation in ischemia-reperfusion. The underlying reasons for the stronger neuroprotective effect of 3D-Exo was further studied using mass spectrometry and transcriptome assays, verifying their effects on immune regulation and cell proliferation. Taken together, our findings demonstrated that GelMA-MN@3D-Exo microneedle can effectively attenuate ischemia-reperfusion cell damage in the MCAO model, which provides a promising therapeutic strategy for ischemia-reperfusion recovery.

Improved scheduling model for a multistage biopharmaceutical process in a multiproduct facility

This study critically evaluates deterministic and stochastic/evolutionary strategies for long-term scheduling of multiproduct facilities in batch and continuous biopharmaceutical manufacturing, as reported in existing literature using discrete-time and continuous-time models. It identifies key limitations in literature model/algorithm, including (i) real-time storage violation, (ii) real-time violation of shelf-life due to its calculation over a single event, (iii) minimum campaign length calculated over single events leading to suboptimal use of resources, and (iv) early product deliveries. To overcome these limitations, a deterministic mathematical model is proposed extending the existing unit-specific event-based model(s) with additional features including (i) modified material balances, (ii) new minimum campaign length constraints captured over multiple events, (iii) new shelf-life constraints captured over multiple events, (iv) new setup constraints based on product sequencing, (v) updated tightening constraints, (vi) updated sales and penalty constraints for late deliveries, (vii) updated bounds, and (viii) updated objective function. These improved features lead to better modeling in terms of handling intermediate and final product storage without real-time violations of storage and shelf-life, handling of initial setup in production tasks, and timely delivery of final products. The proposed improved model yields up to 36 % increase in profit when applied on four literature examples.

Prevalence and barriers to early initiation of breastfeeding among urban poor full-time readymade garments working mothers: a mixed-methods study in Bangladesh

BackgroundEarly initiation of breastfeeding is the initiation of breastfeeding within one hour of birth, which plays a significant role in a born baby’s growth and survival, however its prevalence and predictors among urban full-time readymade garments (RMG) working mothers are not investigated. The purpose of this study is to determine the prevalence and factors affecting early initiation of breastfeeding among urban RMG working mothers.MethodsA sequential explanatory mixed-methods study was conducted between March 2023 and December 2023 in Dhaka, Bangladesh. A total of 452 full-time female RMG workers were included for the quantitative study. Qualitative study was carried out among 30 full-time female RMG workers, four female physicians who were employed in the RMGs, four RMG factory managers, and four local pediatricians.ResultsThe prevalence of early initiation of breastfeeding was 40% among the women. It was significantly associated with various factors, including socio-cultural barriers, the advanced age of the mother (AOR 3.93, 95%CI 1.18, 13.04), lack of education (AOR 6.86, 95%CI 1.11, 42.49), lack of awareness, and cultural practices such as initiating goat milk and honey instead of breast milk. The absence of colostrum feeding (AOR 8.96, 95%CI 4.30, 18.70) and pre-lacteal feeding (AOR 0.06, 95%CI 0.03, 0.11) were significant baby feeding practice-related barriers to early initiation of breastfeeding. Maternal health factors, notably post-delivery sickness, cesarean delivery, and lack of breastmilk production, were revealed as a significant hindrance to the early initiation of breastfeeding explored from qualitative analysis. In addition, RMG factory-related factors that significantly affect early initiation of breastfeeding include a strong focus on production, a busy schedule, and a lack of initiative regarding the early initiation of breastfeeding.ConclusionsThe prevalence of early initiation of breastfeeding among RMG working women is poor. This study emphasizes the need for interventions that address specific challenges of early initiation of breastfeeding faced by working mothers in RMG sectors, including improved lactation education, increased awareness to mitigate cultural barriers, RMG factory-based initiatives to empower female workers early initiation of breastfeeding, and preparing early initiation of breastfeeding -friendly post-cesarean unit at the health care facility.

A Review on various aspects of Regulatory Affairs

In order to guarantee the efficacy, safety, and calibre of medications, medical equipment, and other healthcare supplies, Regulatory Affairs is essential. Anticipating future trends and difficulties in Regulatory Affairs is crucial as the healthcare sector changes due to technological breakthroughs, globalization, and new regulatory paradigms. This abstract examines the consequences of developing fields for regulatory frameworks, including gene treatments, digital health, artificial intelligence, and personalized medicine. It also covers the increased significance of real-world evidence, patient-centric approaches, and international harmonization in regulatory decision-making. In addition, it looks at the difficulties presented by supply chain interruptions, cybersecurity risks, and regulatory divergence in a world that is changing quickly. Stakeholders may effectively navigate the complicated regulatory landscape of the future by embracing innovation, collaboration, and adaptive regulatory methods facilitate the timely delivery of safe and effective healthcare products to patients worldwide.