Processing Chain Research Articles

AI in Healthcare Supply Chain Management: Enhancing Efficiency and Reducing Costs with Predictive Analytics

This paper explores the transformative role of artificial intelligence (AI) and predictive analytics in enhancing operational efficiency within healthcare supply chains. By leveraging AI-driven business analytics, healthcare organizations can optimize inventory management, improve demand forecasting, and streamline supply chain processes. The study presents a comprehensive review of recent advancements, challenges, and opportunities in the integration of AI technologies, focusing on their application in various healthcare contexts. Through systematic analysis of existing literature, the findings emphasize the significance of adopting AI and predictive analytics for effective decision-making, cost reduction, and improved service delivery in healthcare. The research highlights the need for organizations to embrace digital transformation and foster a collaborative approach in the implementation of AI-driven solutions to enhance overall supply chain resilience.

On the localization of reward effects in overlapping dual tasks.

In dual-task (DT) situations, performance deteriorates compared with single-task situations. Such performance decrements are frequently explained with the serial scheduling of the response selection stages constituting a bottleneck. Proof of this assumption stems from the observation that response times for the second task (task 2; RT 2) increase with decreasing stimulus-onset asynchrony (SOA).In this study, we investigated how the reward prospect for task 1 performance affects task 1 and task 2 processing. For that purpose, we relied on the psychological refractory period paradigm (PRP) as a chronometric tool, to determine the locus of the reward effect in the processing chain of both tasks.We obtained improved task 1 and task 2 performance; as indicated by reduced RTs in the reward compared to the no reward condition of task 1 and task 2. Furthermore, the reward effect propagated at short SOA from task 1 onto task 2, suggesting that the locus of the reward effect can be pinpointed before or at the bottleneck of task 1. Importantly, the mean reward effect on task 1 was increased compared to task 2, thus indicating that parts of the reward effect were not propagated onto task 2, therefore affecting task 1 motor processes.In Experiment 2, we tested for the locus of the effect propagation to task 2. Therefore, we implemented a difficulty manipulation of the response selection of task 2. The results indicate that the reward effect is propagated from task 1 onto the response selection stage of task 2.

Blockchain Integration in Critical Systems Enhancing Transparency, Efficiency, and Real-Time Data Security in Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management

Blockchain technology has garnered significant attention for its potential to revolutionize critical systems by enhancing transparency, efficiency, and data security. This review examines the integration of blockchain in three essential domains: Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management. By leveraging decentralized ledgers and smart contracts, blockchain provides a robust framework for real-time tracking, data integrity, and automated compliance, addressing long-standing challenges across these sectors. In Agile Project Management, blockchain fosters seamless collaboration and transparent decision-making, minimizing bottlenecks and improving accountability. In DeFi, blockchain strengthens security for digital transactions and identity verification while offering financial autonomy and mitigating fraud risks. Within Cold Chain Management, blockchain ensures traceability, reduces data tampering risks, and enhances visibility throughout supply chain processes, safeguarding temperature-sensitive goods. This paper evaluates existing blockchain-based applications and frameworks, identifies current limitations, and discusses future opportunities for optimizing critical systems through blockchain. The findings highlight blockchain's transformative role in driving operational efficiency, security, and data transparency across diverse applications, providing a roadmap for industries to harness its full potential in critical environments.

Supplier Visibility in Supply Chain Network and Firm Performance: A Study in Kenya’s Manufacturing Sector

The aim of this study was to establish the effect of supplier visibility on the performance of manufacturing firms in Kenya. The study was anchored on supply chain planning theory. The study utilized a cross-sectional research design. The target population was 561 respondents drawn from the 187 large manufacturing firms in Kenya. Using a stratified random sampling, a sample of 228 respondents was selected. A questionnaire was used to collect data for the study. The data was analyzed using SPSS version 27. The findings revealed that supplier visibility was not effectively embraced among the manufacturing firms in Kenya. The results further revealed that supplier visibility had a significant relationship with performance of manufacturing firms in Kenya (β=0.769; P<0.05). The study concluded that manufacturing firms were declining in performance as a result of inefficient supply chain process and failure to enhance supplier visibility. The study recommended that there is need for managers in supply chain among the manufacturing firms to enhance supplier visibility by incorporating suppliers in their supply chain network planning for them to meet customer needs and promote their performance.

Blockchain for supply chain: performance implications and contingencies

PurposeThis study aims to examine the performance implications of blockchain implementation in the supply chain and explore how blockchain functions and supply chain processes of blockchain implementation moderate the effect on firm performance.Design/methodology/approachUsing 220 blockchain implementations announced between January 2015 and December 2022, we use the event study methodology to estimate the effects of blockchain implementation on the firm value. Regression analyses are conducted to examine the moderating effects of blockchain functions and supply chain processes.FindingsFirst, there is a positive and statistically significant relationship between blockchain implementation in the supply chain and firm value. Second, we find that abnormal returns from blockchain implementation are higher when used with blockchain’s contract automation function and applied in downstream processes, supporting the moderation effects.Originality/valueThe study provides empirical evidence on the effects of the blockchain implementation on firm performance, taking into account the complexity of blockchain functions and supply chain processes. It enriches the current understanding of how blockchain implementation in the supply chain contributes to firm value.

From extraction to end‐uses and waste management: Modeling economy‐wide material cycles and stock dynamics around the world

AbstractMaterial stocks of infrastructure, buildings, and machinery are the biophysical basis of production and consumption. They are a crucial lever for resource efficiency and a sustainable circular economy. While material stock research has proliferated over the last years, most studies investigated specific materials or end‐uses, usually not embedded into an economy‐wide perspective. Herein, we present a novel version of the economy‐wide, dynamic, inflow‐driven model of material inputs, stocks, and outputs (MISO2), and present a global, country‐level application. Currently, MISO2 covers 14 supply chain processes from raw material extraction to processing, trade, recycling, and waste management, as well as 13 end‐uses of stocks. The derived database covers 23 raw materials and 20 stock‐building materials, across 177 countries from 1900 to 2016. We find that total material stocks amount to 1093 Gt in 2016, of which the majority are residential (290 Gt) and non‐residential buildings (234 Gt), as well as civil engineering (243 Gt), and roads (313 Gt). The other nine end‐uses covering stationary and mobile machinery, as well as short‐lived products, amount to 13 Gt. Material stocks per capita are highly unequally distributed around the world, with one order of magnitude difference between low‐ and high‐income countries. Results agree well with similar global country‐level studies. Low data quality for some domains, especially for lower‐income countries and for sand and gravel aggregates, warrant further attention. In conclusion, the MISO2 model and the derived database provide stock‐flow consistent perspectives of the socio‐economic metabolism around the world, enabling multiple novel and policy relevant research opportunities. This article met the requirements for a silver‐gold JIE data openness badge described at http://jie.click/badges.

Be digital to be sustainable! The mediating role of sustainable supply chain practices in triggering the effects of digitalisation on Sustainable Development Goals in the European Union

Research background: European Union (EU) economies need to enhance sustainable supply chains (SSCs) through digitalisation to realise sustainable development goals (SDGs). However, the impact of digitalisation on the SDGs is complex and multifaceted, and the role of SSCs in mediating this relationship is not fully understood. While extant research has delved into the influence of digitalisation on SSCs, predominantly within specific industries or geographic regions, a research gap persists concerning large-N samples and the generalisability of results. Purpose of the article: This study evaluates the role of digitalisation in achieving SDGs along with the mediation of SSCs based on the resource-based view, the triple-bottom-line, and dynamic capabilities theories. Methods: The study has extracted panel data from Eurostat from 2013 to 2022 and evaluated these data through partial least squares structural equation modelling to estimate the association among constructs. The sample covers the EU–27 countries and consists of 270 observations. Digitalisation is operationalised as the use of digital technologies to, for instance, innovate business models, provide new revenue streams and value-producing opportunities, and enhance, streamline, and make supply chain processes more efficient and environmentally sustainable. SSC practices encompass the design, planning, execution, and monitoring of supply chain activities to create value, optimise resources, and minimise environmental impact. Findings & value-added: The findings indicate that digitalisation has a positive association with SDGs and SSC practices. The study also noted that SSC initiatives play a mediating role between digitalisation and SDGs among the EU economies. These interesting insights could direct policymakers to enforce the initiative of digitalisation in SSCs to boost SDGs in EU economies. Although the literature on digitalisation and SSCs has gained significant attention, this is the first study in these domains.

Blockchain-Based Drug Supply Chain Recommendation System (B-DSCRS) with Machine Learning for Supply Chain Management

The pharmaceutical industry has been struggling to keep tabs on its goods across the supply chain for the last decade, which has opened the door for counterfeiters to sell their phoney medications. Integrated product supply chain management mostly focuses on distribution. The pharmaceutical business places a premium on the drug distribution process because of the importance of ensuring the safe handling, storage, and distribution of medical items. The global pharmaceutical sector is facing a significant threat in the form of counterfeit pharmaceuticals. Blockchain technology can manage and monitor the supply chain process with remarkable efficiency when used to its maximum capacity.This paper proposed and implemented a Blockchain-based Drug Supply Chain Recommendation System (B-DSCRS). A pharmaceutical supply chain management system built on the blockchain and a consumer medication recommendation system powered by machine learning comprises our proposed system's two primary components. As a first step in the smart pharmaceutical industry's medication delivery process tracking and monitoring.Conversely, the machine learning module suggests the finest medications for pharmaceutical sector clients. Lastly, our suggested system goes through the testing process to ensure it is efficient and user-friendly.

LIVE MRP (Material Requirements Planning) Impact on Supply Chain

Live Material Requirements Planning (Live MRP) refers to an advanced, real-time approach to managing and optimizing inventory, production, and procurement processes. Unlike traditional MRP systems that update periodically (e.g., daily, weekly), Live MRP integrates dynamic data from across the supply chain and production processes, providing instantaneous updates to material needs, production schedules, and procurement activities. This capability allows companies to respond more swiftly to market fluctuations, production disruptions, and changing customer demands, enhancing operational efficiency, reducing lead times, and improving decision-making

Laser-based disassembly of end-of-life automotive traction batteries: A systematic patent analysis

Battery recycling is a vital component in the decarbonization of the transportation sector. The disassembly step represents a pivotal element within the process chain for battery recycling, as it paves the way for subsequent steps. Semi-destructive disassembly technologies will be key to developing efficient disassembly processes for end-of-life automotive traction batteries. Laser-based separation technologies have emerged as a promising emerging technological approach. Following a systematic search in multiple databases, the obtained records underwent a comprehensive descriptive analysis in terms of both regional and historical context, while key inventors and assignees were identified. Furthermore, citation networks have been identified to provide an overview of the patent landscape and the interrelations within this field. Moreover, an analysis concerning the International Patent Classification and the Cooperative Patent Classification was conducted. An in-depth analysis of relevant patents provides insights into the specific techno-strategic elements currently pursued. The study yields an implication and recommendation framework for research, industry, and policy makers to drive the industrialization of laser-based disassembly technologies as an avenue for efficient end-of-life automotive traction battery disassembly of the future. This framework enables relevant stakeholders to drive their techno-strategic developments in the field of laser-based disassembly, resulting in enhanced laser-based semi-destructive disassembly technologies.

Blockchain in Enterprise Resource Planning Systems: A Comprehensive Review of Emerging Trends, Challenges, and Future Perspectives

Abstract This research paper conducts a systematic review of the integration of blockchain technology with Enterprise Resource Planning (ERP) systems, a burgeoning field at the intersection of advanced technology and business management. The primary objective is to bridge the knowledge gap by synthesizing existing literature, providing insights into the current state, challenges, and potential of blockchain in enhancing ERP systems. The study follows a structured methodology involving four key stages: Literature Retrieval, Literature Screening, Biblio-metric Analysis, and Content Analysis. A comprehensive literature search in the Scopus database resulted in the identification and analysis of 250 scholarly articles, narrowed down to 66 relevant publications. The findings highlight a significant trend towards decentralized ERP solutions, driven by blockchain’s promise of enhanced security, transparency, and efficiency. Key areas impacted by blockchain integration include supply chain management, accounting, security, traceability, purchasing, and process automation within ERP systems. The bibliometric analysis reveals a growing academic interest in this domain, with a focus on scalability, data security, and interoperability. However, the integration faces challenges such as technical complexity, cultural resistance, and regulatory uncertainties. The study concludes that while blockchain presents transformative opportunities for ERP systems, realizing this potential requires overcoming substantial technical and organizational hurdles. Future research should concentrate on developing scalable, interoperable blockchain solutions, tailored to specific industry needs and compliant with regulatory standards, thereby facilitating widespread adoption and maximizing the benefits of blockchain in ERP systems.

Split wooden rods for novel wood-based boards in the construction sector

Wood has been utilized as a building material for thousands of years. Nowadays, its renewable nature and carbon-storing capacity can become important factors in climate change mitigation efforts. This has led to a resurgence of timber engineering in recent years, with impressive multi-story timber buildings worldwide. However, it should not be overlooked that the wood sector will face several challenges in the coming years and decades to pave the way to a leading role of wood in the desired transition toward bioeconomy. Based on the assumption that an increasing demand for wood will make it a more precious resource, a couple of strains will emerge across the entire value chain of wood processing. This calls for innovations to address issues arising from predicted changes in resource provision, to increase material yields, and to promote reuse after the end of life. Our conceptual article proposes a new wood separation and processing method. This approach is inspired by the well-known production of wood shingles and is currently being developed for the implementation of new wood-based products.

Experimental and numerical investigation on the effect of process parameters on joint strength and failure behavior of self-piercing riveted steel/aluminium hybrid joints

To further improve the joint strength and identify the potential failure behavior of self-piercing riveted (SPR) steel/aluminium hybrid joints under shear and cross-tension loading conditions, a simplified 2D-to-3D simulation process chain is proposed. The finite element models (FEM) for the failure process of SPR joints are established in LS-DYNA and verified against experimental results. The effects of rivet strength, sheet material and thickness, and riveting direction on the joint strength and failure behavior of SPR joints are investigated. The results show that when the rivet strength is less than 1.3 GPa, increasing the rivet strength can improve the joint strength of AS joints under shear load and SA joints under cross-tension load. The joint strength of two types of SPR joints increases gradually and then decreases with an increase in thickness ratio Rt. When the steel/aluminium sheet thickness ratio Rsa exceeds 1.47, the aluminium-to-steel direction should be chosen. Increasing material strength can improve the joint strength of two types of SPR joints, while their sensitivities to the material strength vary under different loading conditions. The sheet material, sheet thickness, and riveting direction can change the failure behavior of the joints, while the rivet strength does not alter the failure behavior. This work contributes to understanding the mechanism of joint strength improvement and enhances riveting quality in industrial practice.

Stakeholder-led proactive risk assessment of medication safety in the pharmaceutical supply chain

Abstract Introduction In 2022/23, 1.08 billion medications were dispensed to patients using NHS England, at a cost of £19.04 billion1 . However, Elliot et al (2019)2 estimate every year there are 237 million medication errors at some point of the medication process, with a high associated cost. Increasingly, media is reporting medication shortages of critical medicines3 that can contribute to errors of omission. Medication errors suggests system, tasks and processes should be explored to understand if they have been poorly designed. This paper is a pre-Brexit study that examines the pharmaceutical supply chain with stakeholders. Aim To explore risk to medication safety in the pharmaceutical supply chain using qualitative interviews of stakeholders across the supply chain and proactive risk assessment method SHERPA (Systematic Human Error Reduction and Prediction Approach). Method 1. Qualitative interviews with process models System process models were developed (by literature, field observations and interviewees) and employed to elicit stakeholder perceptions about risk to medication safety in 31 qualitative interviews. Participants included pharmacists, wholesalers, pharmaceutical industry representatives, regulators and policymakers. Ethical approval was granted by Cambridge LREC to include healthcare professionals and 6 patients. Interviews were audio-recorded, transcribed and thematically analysed using N-Vivo. 2. Focus group for SHERPA Six stakeholders participated in the SHERPA focus group4 , including pharmacists and representatives from pharmaceutical manufacturing and wholesale industries. Interview participants were invited and those that agreed, attended. The SHERPA template was completed by the group. The session was audio-recorded, transcribed and thematically analysed using N-Vivo. Results The system models led to a greater understanding of the current system ‘as-is’ and created an overview of the supply chain. SHERPA is a validated method and provided the rigour to risk assess the supply chain process and identify sources of risk. However, the error mode terminology required adjustment to healthcare. Across all supply routes, the main source of risk was failure to supply medicines that caused errors of omission and the risk of counterfeit medicines. Failure to supply resulted from shortages that take place from trading activities that result in stockpiling or exporting of medicines. A lack of robust regulation and parallel imports increased the risk of counterfeit medicines. Stakeholders highlighted deficiencies in the supply chain and poor performance of stakeholders, as medication safety concerns. In order of frequency, the deficiencies include fragmented supply chain; complacency by stakeholders; poor communication and integration across supply chain; and end-user often regarded as the pharmacist, rather than the patient. Discussion and conclusion From the findings, strategies emerged as possible solutions. These included communication of shortages in each component of supply chain; robust counterfeit strategies; use of technology (automation/digital tools); and re-design tasks and processes in dispensaries and wards. Staff training, education, and revalidation of stakeholders is vital. Key limitations in this study include biases that can occur from recruitment strategy and small sample size. The SHERPA method posed terminology problems. In conclusion, this multi-method approach reveals risk and possible solutions to improve safety and reduce cost in the NHS. It is clear this study needs to be repeated to understand the impact of Brexit and current reconfiguration of NHS.

Resource use efficiency: Developing a generic framework for protein production systems and its application on dairy and fish

Resource use efficiency has become increasingly important as the global demand for natural resources continues to grow, necessitating innovative and sustainable utilization strategies. Despite the availability of tools to quantify resource use and environmental impacts, an integrated assessment of total resource use efficiency remains underdeveloped. Addressing this gap, particularly within the context of the protein transition from animal-based to plant-based sources, this work introduces a novel resource efficiency framework. This framework advances current environmental assessments by enabling the precise calculation of efficiency in protein production processes and process chains based on comprehensive resource utilization metrics. It uniquely incorporates the nature of process inputs, including their renewability and circularity, and supports both foreground and life cycle perspectives at the process and process chain levels. To demonstrate its applicability, two case studies—fish and dairy production systems—are evaluated using exergy and mass analyses.

Organizing Scientific Knowledge from Engineering Sciences Using the Open Research Knowledge Graph: The Tailored Forming Process Chain Use Case

Organizing Scientific Knowledge from Engineering Sciences Using the Open Research Knowledge Graph: The Tailored Forming Process Chain Use Case

Complementary Machining – Machining Strategy for Surface Modification: A Review

All fabrication techniques utilized to manufacture metallic parts modify the surface integrity of the part. Complementary machining is a relatively recent machining strategy characterized by combining metal cutting and mechanical surface treatment. Typically, it implies that after conventional machining, the cutting insert is used reversely to modify the surface by local plastic deformation. To improve product performance, mechanical surface treatment is an additional phase in the manufacturing process chain that usually results in longer production times and higher costs. As a result, a variety of hybrid techniques have been created, such as complementary machining, which has the benefit of using conventional machine tools and their associated cutting tools. The study on complementary machining is reviewed in the article. The main focus is to assess the viability of complementary machining to modify surface integrity for enhanced properties by specifically establishing its effect on tool wear, surface roughness, microhardness, fatigue, microstructure, and residual stress state.

Reproduction of the chain process of debris flow blocking river at a catchment scale: a numerical study

Reproduction of the chain process of debris flow blocking river at a catchment scale: a numerical study

Computational analysis of the Logistics Supply Chain from a global trade perspective

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

On-demand reprogramming of immunosuppressive microenvironment in tumor tissue via multi-regulation of carcinogenic microRNAs and RNAs dependent photothermal-immunotherapy using engineered gold nanoparticles for malignant tumor treatment

The frequent immune escape of tumor cells and fluctuating therapeutic efficiency vary with each individual are two critical issues for immunotherapy against malignant tumor. Herein, we fabricated an intelligent core-shell nanoparticle (SNAs@CCMR) to significantly inhibit the PD-1/PD-L1 mediated immune escape by on-demand regulation of various oncogenic microRNAs and perform RNAs dependent photothermal-immunotherapy to achieve precise and efficient treatment meeting the individual requirements of specific patients by in situ generation of customized tumor-associated antigens. The SNAs@CCMR consisted of antisense oligonucleotides grafted gold nanoparticles (SNAs) as core and TLR7 agonist imiquimod (R837) functionalized cancer cell membrane (CCM) as shell, in which the acid-labile Schiff base bond was used to connect the R837 and CCM. During therapy, the acid environment of tumor tissue cleaved the Schiff base to generate free R837 and SNAs@CCM. The SNAs@CCM further entered tumor cells via CCM mediated internalization, and then specifically hybridized with over-expressed miR-130a and miR-21, resulting in effective inhibition of the migration and PD-L1 expression of tumor cells to avoid their immune escape. Meanwhile, the RNAs capture also caused significant aggregation of SNAs, which immediately generated photothermal agents within tumor cells to perform highly selective photothermal therapy under NIR irradiation. These chain processes not only damaged the primary tumor, but also produced plenty of tumor-associated antigens, which matured the surrounding dendritic cells (DCs) and activated anti-tumor T cells along with the released R837, resulting in the enhanced immunotherapy with suppressive immune escape. Both in vivo and in vitro experiments demonstrated that our nanoparticles were able to inhibit primary tumor and its metastasis via multi-regulation of carcinogenic microRNAs and RNAs dependent photothermal-immune activations, which provided a promising strategy to reprogram the immunosuppressive microenvironment in tumor tissue for better malignant tumor therapy.