Research Articles (Industrial and Systems Engineering)

Permanent URI for this collectionhttp://hdl.handle.net/2263/2374

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Advancing improvements to enterprise systems with a participatory system dynamics method using figma
Hussain, Huda; De Vries, Marne (South African Institute of Industrial Engineers, 2025-12-08)
ENGLISH : System dynamics (SD) offers a whole-system perspective to model complex, non-linear behaviour and to assess the impact of interventions in multiple performance areas. To address the difficulties of ill-defined SD concepts, a meta model for enterprise systems dynamics (MMESD) was previously developed and refined, resulting in the e1MMESD. This study applied the e1MMESD in a participatory system dynamics method (PSDM), enabling stakeholders collaboratively to build knowledge, manage uncertainty, and identify leverage points for system improvement. The PSDM, developed as a design science research artefact, is structured in four phases, and developed using the Figma modelling tool to support online collaboration. A single application of the PSDM resulted in both causal loop diagrams (CLDs) and causal loop stock and flow diagrams (CLSFDs) as final deliverables. The diagrams were tested and refined in workshops with five projects in agriculture, healthcare, manufacturing, and industrial services. The findings indicate that the proposed participatory method offers a flexible, replicable approach to improving an enterprise system, while providing valuable insights into how participatory practices could foster system understanding and the effect of suggested interventions.
Event-based vision application on autonomous unmanned aerial vehicle : a systematic review of prospects and challenges
Akanbi, Ibrahim; Ayomoh, Michael Kweneojo (MDPI, 2025-12-22)
Event camera vision systems have recently been gaining traction as swift and agile sensing devices in the field of unmanned aerial vehicles (UAVs). Despite their inherent superior capabilities covering high dynamic range, microsecond-level temporary resolution, and robustness to motion distortion which allow them to capture fast and subtle scene changes that conventional frame-based cameras often miss, their utilization has yet to be widespread. This is due to challenges like insufficient real-world validation, unstandardized simulation platforms, limited hardware integration and a lack of ground truth datasets. This systematic review paper presents an investigation that seeks to explore the dynamic vision sensor christened event camera and its integration to (UAVs). The review synthesized peer-reviewed articles between 2015 and 2025 across five thematic domains, datasets, simulation tools, algorithmic paradigms, application areas and future directions, using the Scopus and Web of Science databases. This review reveals that event cameras outperformed traditional frame-based systems in terms of latency and robustness to motion blur and lighting conditions, enabling reactive and precise UAV control. However, challenges remain in standardizing evaluation metrics, improving hardware integration, and expanding annotated datasets, which are vital for adopting event cameras as reliable components in autonomous UAV systems.
Evaluating and extending the meta model for enterprise systems dynamics
Hussain, Huda; De Vries, Marne (Springer, 2026-06-16)
Systems dynamics (SD) takes a whole-system perspective to model the nonlinear behaviour of complex systems, offering the potential to understand enterprise system behaviour, and the effect of interventions and enterprise re-designs when addressing multiple performance areas. Since SD concepts are ill-defined, a meta model for enterprise systems dynamics (MMESD) was developed, applying the initial version of the MMESD to an existing case, where the case was modelled with the modelling software, named Vensim. The initial MMESD required further evaluation, regarding its ease-of-understanding and its comprehensiveness. Using design science research (DSR), we evaluated the ease-of-understanding of the initial MMESD, involving practitioners. In terms of comprehensiveness, the initial MMESD was developed without considering meta model implementations within multiple SD modelling tools. This article thus also investigates the use of SD concepts in different SD modelling tools, highlighting the differences in the use of symbolic formalisms. The results regarding ease-of-understanding indicated limited understanding for: (1) identifying a feedback loop as reinforcing or balancing; and (2) using an attribute to extend the initial MMESD, highlighting limited understanding of the language used for expressing the MMESD concepts. Results related to the comprehensiveness of the MMESD, indicated that new concepts were identified for an extended MMESD, i.e. eMMESD, applied to an existing teacher education faculties case in Croatia as a demonstration. The eMMESD is more comprehensive in representing SD concepts than the initial MMESD, also providing additional guidance to the practitioner, using the eMMESD to guide SD modelling.
The operational excellence research landscape in Africa : a scoping review
Doyer, Ilse; Odendaal, Pelayia (Emerald, 2026-02)
PURPOSE : This paper aims to be a catalyst for operational excellence (OpEx) implementation and research on the African continent by reviewing the proliferation of ten integrated OpEx approaches. The analysis and review of the literature can aid both researchers and practitioners in identifying research and implementation gaps as well as studies complementary to their fields of interest. DESIGN/METHODOLOGY/APPROACH : A systematic eight-step process was followed to screen 353 publications on OpEx in Africa, of which 101 Scopus and Web of Science cataloged articles were descriptively analyzed. The PRISMA-SCR checklist was used to ensure rigor in the presentation of the scoping review. FINDINGS : Total quality management (20.8%), business process reengineering (12.9%) and Lean Six Sigma (12.9%) were the most prevalent approaches in the literature sample, and Six Sigma and total productive maintenance were the least prevalent. The sample consisted mostly of case studies, but in 15 different host industries, with manufacturing making up 35.6% of the sample. South Africa was the most active country in OpEx research, contributing 54.5% of the sample, and along with Nigeria (15.8%), Ghana (5.9%), Zimbabwe and Ethiopia (4.0% each) made up 84.2% of the sample. More than two-thirds (68.4%) of the 57 African countries had no detectable presence in the literature sample. ORIGINALITY/VALUE : No scoping reviews on OpEx in Africa were identified among the initial literature search results of 1,100 articles, meaning that an overview of OpEx research in Africa is either non-existent or rare, and that this scoping review presents a unique and/or rare synthesis on OpEx in Africa.
Development of integrated framework for automated construction progress sensing, monitoring and evaluation
Olowe, Mofiyinfoluwa Tobi; Ayomoh, Michael Kweneojo (MDPI, 2025-11-07)
The construction industry is increasingly adopting digital technologies to enhance productivity and efficiency, in alignment with the principles of Construction 4.0 (C4). The progress and advances recorded thus far are largely due to advancements in cyber-physical systems (CPS), computational processing power, deep learning solutions, robotics, and other related technologies. However, a major challenge in this research space is the lack of an integrated solution for both the interior and exterior construction environments, which has led to fragmented data, hindering efficiency. Several researchers have proposed frameworks in recent years that focused on either indoor or outdoor construction environments; this approach has resulted in the creation of siloed information, to the detriment of the C4 ideals and principles. In this study, a comprehensive system architecture for raw data captured using sensors and other inputs to provide useful insight for the construction team and stakeholders was mapped out. This study presents an integrated framework of various technologies for both indoor and outdoor construction environments. The solution provided for localisation algorithms and technologies such as Simultaneous Localisation and Mapping (SLAM), odometry, and inertial measurement unit (IMU) devices. The unified 5-level Cyber-Physical Systems (CPS) architecture was used as the primary architecture, and it was compared with the IoT Architecture layers in terms of data analytics and management perspectives. The Digital Twin (DT), which sits at the cyber level of the architecture, warehouses and tracks in real-time the dynamic complexities of the construction site throughout the project life cycle, serving as the single source of truth for the project. This system architecture and framework presented in this research contributed towards advancing the field of construction automation by offering a scalable solution for efficient construction in project management.
Intelligent chatbot system design, development, and deployment for client queries : efficient and effective perception and cognition
Sebola, Tlou; Ayomoh, Michael Kweneojo; Ndlovu, Brain Ndumiso (MDPI, 2025-11-17)
The recent synergistic explosion of artificial intelligence and the world of machines, in a bid to make them smarter entities as a result of the fourth industrial revolution, has resulted in the concept of chatbots, which have evolved over the years and gained heightened attention for the sustainability of most human corporations. Organisations are increasingly utilising chatbots to enhance customer engagement through the process of agent-based autonomous sensing, interaction, and enhanced service delivery. The current state of the art in chatbot technology is such that the system lacks the ability to conduct text-sensing in a bid to acquire new information or learn from the external world autonomously. This has limited the current chatbot systems to being system-controlled interactive agents, hence, strongly limiting their functionalities and posing a question on the purported intelligence. In this research, an integrated framework that combines the functionalities and capabilities of a chatbot and machine learning was developed. The integrated system was designed to accept new text queries from the external world and import them into the knowledge base using the SQL (Structured Query Language) syntax and MySQL workbench (version 8.0.44). The search engine and decision-making cluster was built in the Python (version 3.12.7) coding environment with the learning process, solution adaptation, and inference, anchored using a reinforcement machine learning approach. This mode of chatbot operation, with an interactive capacity, is known as the mixed controlled system mode, with a viable human–machine system interaction. The smart chatbot was assessed for efficacy using performance metrics (response time, accuracy) and user experience (usability, satisfaction). The analysis further revealed that several self-governed chatbots deployed in most corporate organisations are system-controlled and significantly constrained, hence lacking the ability to adapt or filter queries beyond their predefined databases when users employ diverse phrasing or alternative terms in their interactions.
A structural model for assessing the impact of lean-green barriers on sustainable performance
Machingura, Tinotenda; Adetunji, Olufemi; Maware, Catherine (Emerald, 2025-11)
PURPOSE : The purpose of the study is to examine the impact of internal and external barriers on Lean-Green manufacturing during its post-implementation phase. Examining the impact of Lean-Green manufacturing on the environmental, economic and social performance of organisations is also an aim of the study. The study further explores the inter-relationships between environmental, economic and social performance. DESIGN/METHODOLOGY/APPROACH : Data was gathered from the Zimbabwean manufacturing industry, of which 302 valid responses were obtained and analysed through structural equation modelling using SMART PLS. FINDINGS : The results showed that both internal and external barriers impede organisations from improving economic, social and environmental performance measures, and hence, deserve attention. RESEARCH LIMITATIONS/IMPLICATIONS : The study concentrated on Zimbabwe’s manufacturing industry; hence, the results may need further validation before they can be adopted by other countries and industries. PRACTICAL IMPLICATIONS : Through analysing the impact of internal and external barriers on Lean-Green, organisations can understand which barriers greatly affect them and they can allocate resources accordingly to address them. ORIGINALITY/VALUE : Existing studies focused on identifying and ranking the barriers faced during Lean-Green implementation. This study identifies the Lean-Green barriers that are faced post-implementation and examines their relationship with Lean-Green Manufacturing and sustainable performance. Thus, outlining a clear picture of the extent to which these barriers hinder the attainment of sustainable development improvements.
An assessment of the relationship between human dimensions, hard lean practices and operational performance: moderation role of lean duration
Machingura, Tinotenda; Maware, Catherine; Adetunji, Olufemi (Emerald, 2026-05-07)
PURPOSE : Organizations are embracing lean manufacturing (LM) to enhance their operational performance. Extant research recommends that manufacturing organizations align hard lean practices (HLP) with soft lean practices (SLP), such as human dimensions. We analyzed the impact of HLP on the association between SLP and operational performance with lean duration as a moderator. DESIGN/METHODOLOGYy/APPROACH : We utilized data collected from 211 manufacturing organizations in Zimbabwe. We used structural equation modeling (SEM) to test the proposed hypotheses. FINDINGS : The study results showed that HLP practices mediate the relationship between SLP and operational performance. Moreover, lean duration moderated the association between HLP practices and operational performance and between SLP and operational performance. ORIGINALITY/VALUE : Although LM utilizes HLP and SLP, the literature does not fully explore the effect of SLP on operational performance. Furthermore, the mediatory role of HLP needs to be investigated so that organizations are guided accordingly on how to integrate them with SLP. Examining the perceived moderating role of lean duration on the association between LM and operational performance and between human dimensions and operational performance equips organizations with a better understanding of the success of lean implementation.
Staying true to the data : a visual and quantitative approach to showcase coding rigour and theoretical saturation
Doyer, Ilse; Ayomoh, Michael Kweneojo (Institute for Research and Theory Methodologies, 2025-06)
This paper describes a data-based and transparent approach that was followed during classic grounded theory data analysis to ensure rigor and theoretical saturation. Firstly, a visual approach was followed to ensure that the theory discovery stayed as close to the story told by the data set as possible, thus ensuring both rigor and accuracy. Secondly, process data in the form of a coding rate time study and theoretical contribution rate, were tracked to monitor theoretical saturation objectively. The presented approach offers a novel approach to showcasing classic grounded theory rigor during the data coding process, as well as a way to prove that theoretical saturation was reached. The approach presented in this paper thus provides grounded theory researchers with a way in which to both ensure and defend the rigor and accuracy of their research.
A functional classification and feature repository for participative enterprise modelling tools : an AI-complemented multivocal literature review
Venter, Anthea; De Vries, Marne (Taylor and Francis, 2026)
Selecting appropriate modeling tools for participative enterprise modeling (PEM) remains challenging in an era defined by digital collaboration and remote work, partly due to the absence of a comprehensive overview of tool features. To address this gap, we conducted a multivocal literature review (MLR) to develop a repository of PEM tool features. Thirteen primary publications were analyzed, sourced from four academic databases, complemented by searches in SciSpace, Elicit, and through forward and backward snowballing. Some tools identified in academic literature are no longer freely available, and many popular collaborative whiteboard tools were not extracted from our primary publications. To address this, features from grey literature were reviewed and used to enhance our repository. As a secondary contribution, we explore the potential of artificial intelligence (AI) to support the process. Future work should prioritize ongoing updates to the repository and the use of automated methods for literature screening and feature extraction.
Using system dynamics modelling to optimize energy and water efficiency of decoupled aquaponic systems : a South African perspective
Roux, Adriaan J.G.; Ayomoh, Michael Kweneojo; Yadavalli, Venkata S. Sarma; Bansal, Ramesh C. (Elsevier, 2025-07-11)
Despite being energy and water proficient, the practice of aquaponics has remained underdeveloped and underutilized in a poor power generating continent like the African continent and a water scarce society like the Republic of South Africa. As the population of humans on the globe continues to grow geometrically with climate change also being aided, more proficient and safe means of food security premised on energy and water efficiency is becoming the prerogative of governments across different nations. This research has presented a system dynamics model of a decoupled aquaponics system to investigate the sensitivity of parameters in the design of aquaponics systems in the Republic of South Africa. Two major driving variables considered in this research include energy and water utilization for efficient design. A couple of ventilation flow, heating and energy based models were built into the system dynamics model for the conduct of simulation. The results revealed that the top performing countries in respect of energy and water efficiency include locations with hot humid climates such as Brazil, Nigeria and Malaysia. In South Africa, Durban was the best performing city with a peak energy demand of 18.4 MW and a total yearly energy usage of 4550 MW. Durban had a 7.3 % higher cumulative energy compared to Brazil. Durban had a net water return of 124.8. Given the humid and hot climate in the city of Durban, it is considered to be competitively suitable for aquaponics operations. Other regions in South Africa could still be suitable to operate aquaponics systems however, this might be less energy and water efficient. The outcome of this research can be utilized by local governing authorities to ensure sustainable policy design and implementation.
Stochastic analysis of a system of two interconnected inventories
Yadavalli, Venkata S. Sarma; Tshinangi, Kapya; Adetunji, Olufemi (MDPI, 2025-12-05)
This paper considers a continuous review inventory system for two interconnected product types, 1 and 2. Product type 1 is purchased from an external agency, whereas type 2 is manufactured in-house through a sequential batching process. The maximum stock position attainable by type 1 is 𝑆1 and that of type 2 is 𝑆2 . Unit demands arise independently for the two products, where type 1 demand arrives following a Poisson process with rate 𝜆1 and that for product B also follows a Poisson process with rate 𝜆2. At the instance of the stock level of type 1 dropping to zero, it is replenished instantaneously to the maximum level 𝑆1 , such that the stock level is never zero, and hence all demands for type 1 product are satisfied. The production machine attached to type 2 stops manufacturing immediately when its stock level reaches 𝑆2, and resumes immediately when the stock level drops to 𝑆2−1. In the event of the type 2 product not being available when demand arrives, it is substituted with the type 1 product with probability p. The production time for a single unit of type 2 is exponentially distributed with mean 1𝛾. We identify the underlying Markov process and analyse the performance of the interconnected inventory system.
An inventory model for growing items with imperfect quality, deterioration, and freshness- and inventory level-dependent demand under carbon emissions
Tshinangi, Kapya; Adetunji, Olufemi; Yadavalli, Venkata S. Sarma (MDPI, 2025-12-12)
Inventory models have evolved to incorporate a wide range of realistic factors, including growing items, imperfect quality, deterioration, and sustainability concerns. While these areas have received significant individual attention, no model has yet integrated the complexities of growing items, imperfect quality, deterioration, and carbon emissions. This study addresses this gap by introducing an economic order quantity (EOQ) model for growing items that simultaneously accounts for imperfect quality, deterioration, carbon emissions, and a demand rate that is influenced by both stock levels and the freshness condition. The goal is to determine the replenishment cycle and the optimal order quantity that will maximise profit. A numerical example is presented to illustrate the model’s feasibility. A sensitivity analysis on key parameters is also conducted to provide critical managerial insights. The results reveal that the shelf life of items and the scaling parameter of demand are among the most influential factors of profit, causing up to 150% and 112% increase in profit, respectively. The findings also indicate that deterioration significantly impacts system profitability by up to −45%. Another critical insight is that profit decreases by up to 80% when the weight of the growing items increases. Furthermore, emissions can be most effectively reduced by focusing on the feeding process, which represents the most impactful factor for improving sustainability, whereas emissions from the screening process, purchasing, deterioration, and storage hold minimal financial consequence.
An economic order quantity model for imperfect and deteriorating Items with freshness and inventory-level-dependent demand
Coghlan, Deidre Ann; Adetunji, Olufemi; Sebatjane, Makoena; Kapya, Tshinangi Fabrice (South African Institute of Industrial Engineers, 2025-08-29)
ENGLISH : The sale of many products is influenced by the characteristics of the products and the behaviour of the consumers. This is particularly true of food items. Consumers of most food items want them fresh; thus, while items that are edible but have lost some of their freshness might be sold, the demand usually drops, and the closer the expiry date, the lower the demand for such products. Another factor that is known to affect the sale of many items is the attractiveness of the stocking pattern. Seeing a large stock of consumable items tends to attract consumers; hence the stock level dependence of demand. An additional characteristic of such products is that they continue to deteriorate; thus affects both the quality and quantity of such items, as the overly deteriorated ones are removed from the stock of saleable items. Consequently, the stock level reduces owing to both demand and deterioration. This description fits many agricultural products such as fruits and vegetables. Another characteristic of such products is the possibility of their being imperfect when they are received, as some stock might be damaged by harvesting, handling, or transportation. In this research, we develop a mathematical model to determine the optimal lot size for an item having all these characteristics, with the profit function as the model objective. We used a case of banana as the numerical illustration. Sensitivity analyses of important model parameters were conducted to demonstrate the model’s robustness. The findings were that the date of expiry, the scale of demand, and the selling price of perfect products were the main constituents that affected their profitability. This model should find ready application in most stores where fresh consumable food items such as fruits and vegetables are managed.
A two-echelon supply chain inventory model for perishable products with a shifting production rate, stock-dependent demand rate, and imperfect quality raw material
Tshinangi, Kapya; Adetunji, Olufemi; Yadavalli, Venkata S. Sarma (MDPI, 2025-06)
This model extends the classical economic production quantity (EPQ) model to address the complexities within a two-echelon supply chain system. The model integrates the cost of raw materials necessary for production and takes into account the presence of imperfect quality items within the acquired raw materials. Upon receipt of the raw material, a thorough screening process is conducted to identify imperfect quality items. Combining imperfect raw material and the concept of shifting production rate, two different inventory models for deteriorating products are formulated under imperfect production with demand dependent on the stock level. In the first model, the imperfect raw materials are sold at a discounted price at the end of the screening period, whereas in the second one, imperfect items are kept in stock until the end of the inventory cycle and then returned to the supplier. Numerical analysis reveals that selling imperfect raw materials yields a favourable financial outcome, with an optimal inventory level 𝐼1 = 11,774 units, optimal cycle time 𝑇=2140 h, and a total profit per hour of USD 183, while keeping the imperfect raw materials to return them to the supplier results in a negative profit of USD −4.44×103 per hour, indicating an unfavourable financial outcome with the optimal inventory level 𝐼1 and optimal cycle time T of 26,349 units and 4702.6 h, respectively. The findings show the importance of selling imperfect raw materials rather than returning them and provide valuable insights for inventory management in systems with deteriorating products and imperfect production processes. Sensitivity analysis further demonstrates the robustness of the model. This study contributes to satisfying the need for inventory models that consider both the procurement of imperfect raw materials, stock-dependent demand, and deteriorating products, along with shifts in production rates in a multi-echelon supply chain.
Business size moderation and internal factors mediation impacts on SME business performance
Rampyapedi, Koketso P.; Adetunji, Olufemi (AOSIS, 2024-11-30)
BACKGROUND : Small businesses are important for the economy of any country, including South Africa. Small and medium enterprises (SMEs) serve as a valuable engine for growth, innovation, new product development and job creation in the economy. AIM : This research examines business size as a moderator of the effects of the external business environment and the organisation of internal resources on the performance of SMEs in South Africa. SETTING : Data for this study were collected using a survey questionnaire from 465 enterprises in South Africa across various industries. METHODS : The study utilised a higher-order structural equation modelling and analysed data obtained from 465 complete responses using SmartPLS 4. RESULTS : Findings indicate that business size moderates the relationship between business resources and performance. The study further demonstrated that external factors directly impact the management, allocation and utilisation of internal business resources. CONCLUSION : Both internal and external resources are found to influence business performance, with internal resources partially mediating the effect of external factors on business performance. The social capital construct suggests that for a better performance of business organisations, businesses must strive for diversification of their network channels and form meaningful associations within the industry they operate. CONTRIBUTION : The study emphasises the importance of the internal resource factors to the success of businesses, irrespective of their size. Structural reforms and policies should be strengthened in supporting and enabling SMEs to grow their businesses to gain continued economic growth.
Developing a COVID-19 impact assessment model for the education sector
Machingura, Tinotenda; Muyavu, Ashleigh Tatenda (Emerald, 2025-12)
PURPOSE : This study aims to develop an impact assessment model that can be used by educational institutions to investigate the effect of Covid-19 on the performance of students and educators. DESIGN/METHODOLOGY/APPROACH : A systematic literature review was used to identify the models used to assess the impact of Covid-19 in the education sector. Most of these models used structural equation modelling (SEM), and hence, the developed conceptual model was based on SEM. The model was validated through a pilot study conducted in Zimbabwe’s education system. Questionnaires were sent to different educational institutions, and 69 responses were obtained, and they were analysed utilising SMART PLS 4. FINDINGS : The models in the literature are all different and hence create confusion in finding the best model to use. The authors developed a standard measurement model with lockdown, curfew, online learning and performance latent variables. The pilot study results indicated that curfew, lockdown and online learning affect performance. RESEARCH LIMITATIONS/IMPLICATIONS : The study focused on developing a measurement model for the education sector; however, this model cannot be used for other industries, such as manufacturing and agriculture, without further research. ORIGINALITY/VALUE : The models in the literature concentrated more on online learning. This study included lockdown and curfew, as they cannot be left out when examining the effects of Covid-19. This allows educational institutions to fully examine the impacts of Covid-19 on the performance of students and educators.
Modelling, analysis and sensory metrication towards a quantitative understanding of complexity in systems
Ball, Melissa Claire; Ayomoh, Michael Kweneojo (MDPI, 2024-11)
Modelling and metrication of the complexity of systems have occupied a growing and largely underdeveloped problem space in the literature of complex systems. In this research, preliminary results depicting the complexity of a service system premised on a tertiary institution of learning is presented. The concept deployed focused on modelling the trio core entities viz: functional elements, physical elements and the intricacy of connectivity associated with the flow of signals in the normal systemic operations. The numerous activities depicting diversity and multiplicity were holistically enumerated prior to sensing and metrication. The outcome of this research underscores effectiveness in the proposed model.
Revisiting shift cipher technique for amplified data security
Verma, Raksha; Kumari, Anjali; Anand, Adarsh; Yadavalli, Venkata S. Sarma (Bon View Publishing, 2024-02)
Ever sincemanualwork is overtaken by technology, the rapid advancement in the technologies for performing all kinds ofwork online has created newpossibilities for the organizations and institutions of all types.But this has also created opportunities for attackers and opponents by reducing the powers of existing controls over data sharing. All private, public, and any other sectors are using the internet for sharing their data. Transmission of unencrypted data over the internet is not secure as it posesmany privacy concerns as they can be easily hacked andmisused by any unintended person. So, everyone is concerned about safe and secure ways of data transmission in order to avoid leak of private data, as hackers always try tochase the transmitted data and torecover it, and thereforevarious different techniques are developed inorder tomake data transmission more secure. Encryption is essential to protect and prevent such lapses in the transmission of sensitive information over the internet and any other networks. In this paper, the author has worked on a better version of Caesar cipher and invented a method in which modular arithmetic is used to convert plaintext into ciphertext in order to amplify and to bolster up the security of the sensitive data or information, and the author composed the decryption method in such a way that it is no way related to encryption by involving the divisibility tests and arithmetic modulo.
Optimisation strategies and technological advancements for sustainable direct reduction iron production—a systematic review
Nyakudya Ncube, Ratidzo Yvonne; Ayomoh, Michael Kweneojo (MDPI, 2025-03)
This systematic review examines optimisation strategies and technological advancements to foster sustainable direct reduction iron (DRI) production. The evaluation encompassed a meticulous review of journal articles, industrial reports, and conference papers published between 2002 and 2025, ultimately identifying 65 pertinent studies. A qualitative thematic analysis of the optimisation strategies enabled the identification of three primary themes: life cycle assessment strategies, modelling tools, and technological innovation strategies. This review highlights innovative approaches to using alternative reductants such as biomass and hydrogen, incorporating renewable energy sources in the process, and the economic feasibility of adopting these optimisation strategies. The research findings indicated that there is an urgent need to enhance waste management strategies, especially for coal-based reduction processes, as they are linked to environmental issues. Hydrogen-based reduction has been identified as an innovative methodology for waste control with the potential to reduce carbon dioxide emissions by up to 90%, though it has its limitations. The Circular Economy approach has been proposed as a viable strategy to reduce waste generation and extend the lifespan of materials used in the DRI process. This review provides essential insights on resource optimisation and utilisation and promotes technological innovation to improve the sustainability of DRI.

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