Multinational business optimization: a systems approach

Abstract: Current developments in technology together with the global village concept have contributed to large international corporates becoming a reality. Growth and centralization, results in the agglomeration of cultures, geographical locations, business units and specialized divisions into a “perceived” single unit. Total business optimization requires the enablement of all business process from the smallest operational unit to corporate, from inbound, in process to outbound functions inclusive of total business management. On a global optimization view the two dimensions of delivery include “shop floor to top floor” and “global, end to end” perspectives. The current operations of individual production units, independent of global subsidiaries are a distinct challenge as independent operations divert the potential of global assets/ supply optimisation. Crucially is the fact that research, technology development, asset optimisations, planning, corporate (strategy, investment planning, and finance), supply chain and other function of large multinationals are usually centralised. These central functions operate independently with crucial dependencies on operational, site to global, information. The current practice of manual/paper base information is limited specifically to human dependencies such as, obtainability, accuracy, time, and interpretation. These key issues result in a multidimensional and multilayer challenge of total business optimization. Total business optimization must include, but not be limited to, production, supply chain, human resources, finance, Information management, plant control, research, technology development, together with sales and distribution. The additional complexity of multisite operations must also be included in order to achieve true global, end to end, optimization. There has been development in deployment of limited solutions but replication and accelerated delivery can only be addressed via a standardized approach. This research proposes a standardization, global system approach to this challenge from Enterprise Resource Planning through manufacturing systems down to instrumentation

Discrete event modelling for evaluation and optimisation of power utility energy demand

Purpose: The cost and environmental impact of energy is driving better quantification of energy utilization in a business context. Determining an entire business electrical energy usage, inclusive of core operations and support activities, in a singular evaluation protocol is a challenge. The challenge is exasperated when changes occur in the business, where every change implies significant rework of the business energy calculations. This study develops a holistic energy determination model for the entire business requiring minimum inputs for energy re-calculation, when aspects of the business changes. Design/methodology/approach: The research adopts a quantitative approach enabled through a Discrete Event Model. The model is developed based on the activities performed in every functional area of the business. The activities are captured using business process science. The processes are then developed into a DES Model. The model development cycle includes data collection, model development and configuration, model validation and scenario models for optimization. Findings: A coal fired power generation business, with multiple sites is comprehensively simulated to evaluate the baseline electrical energy demand and associated CO2 emissions. The results are captured at various levels of the business including; Enterprise; site, business function and equipment level. The generation sites operational functions are identified as major electrical energy consumers. The adoption of Industry 4.0 technologies of Internet of Things, Big Data Analytics, mobility and automation demonstrate energy savings of 1% of total site demand. As the Industry 4.0 technologies are applied to a limited number of processes, the results demonstrate the capability of these technologies having a significant impact on electrical energy demand and CO2 emission when applied to a broader spectrum of business processes. Research limitations/implications: The research is limited to a multi-site energy generating company, which is a coal to energy business. Practical implications: The research has significant practical implications, mostly on the mechanisms to evaluate business energy utilisation. The ability to include all areas of the business is a key practical differentiator, as compared to traditional models focusing on operations only. Originality/value: The model is unique in that it is a model that is system agnostic to any production configuration, most especially changes in configuration. This implies that the model can be easily and quickly adapted with changes in the business. This implies the model proposed would be significantly more adaptable when compared to traditional approachesPeer Reviewe

Policy (In)Consistency and Sustainable Development Goals in Africa: A Systematic Literature Review

The attainment of Sustainable Development Goals hinges on the alignment of SDGs policies. This systematic literature review delves into the intricate relationship between policy inconsistency and sustainable development goals in Africa. Through this study, we unveil the challenges, implications, and the potential pathways that emerge at the intersection of policies and the quest for sustainable development in Africa. Our investigation takes a close look at the diverse dimensions of policy coherence, encompassing economic, social, and environmental considerations, and how these dimensions impact the progress of SDGs. Employing a systematic review approach, we meticulously filtered through 1745 results from databases, selecting 353 articles for a comprehensive analysis. Our findings underscore the significant role that policy inconsistency plays in impeding the attainment of SDGs in Africa. We propose an approach anchored on the alignment of SDGs policies and each goal of SDGS for the attainment of the 2030 SDGs agenda in Africa

Reverse logistics framework for PET bottles

Abstract: Reverse logistics (RL) is an engineering strategy used by manufacturing companies to develop environmental sustainability through recycling. The result of not having appropriate legislation and frameworks in Zambia, specific to RL for plastic bottles, huge volumes of Polyethylene Terephthalate (PET) bottles are dumped on the Environment. Only 30% of the waste generated, in Zambia, is collected for disposal in dumpsites and the remaining 70% is not recovered. Of the 30% waste collected, there is no data to indicate the exact amount of PET bottles disposed. This paper focuses on analyzing RL activities performed by beverage manufacturing companies in conjunction with community involvement. Examining the regulations set by the regulatory bodies in monitoring waste management issues. Three separate questionnaires are issued, one for the beverage companies, one for the regulatory body and one for the municipality. Structured interviews and direct observations were also used. The results indicate that, RL of PET bottles is not practiced by the beverage companies. However the companies recognize the importance of recycling PET plastic bottles and have printed symbols of recycling on their bottles. Measures taken to protect the environment indicate regulations from the regulatory body are in place though not effectively enforced on PET plastic waste This paper focuses on analyzing the data collected via the three tier questionnaires and providing some insights into options to implement RL, within the Zambian constraints. A Container Deposit logistics Refund Legislation (CDRL) framework was developed and proposed for use in the recovery of PET bottles and any other recyclables

The Impact of lean on the mining industry : a simulation evaluation approach

Abstract: The mining industry, especially in Southern Africa, is experiencing significant uncertainty and volatility, and it has become important for mining organizations to find ways to reduce cost and improve operational efficiency. The Lean principle mainly aims to reduce waste specific to resources, time and cost and has slowly been adapted into the mining industry. The main objective of the study was to evaluate the impact of applying the Lean principle in a mining company using simulation modeling. The study commences with literature review so as to explore the most recent Lean application in mining. A case study was utilized to identify and examine the production flow that exists on the diamond production set up. Sample data was collected, and a current state Value Stream Map was constructed. A simulation model of the production set up of the diamond mine was configured and simulation-optimization techniques are utilized. The study contributes to the understanding of the link between the Lean principle and efficient execution of mining operations. The study also illustrates simulation modeling as a tool to compliment Lean evaluation

Hospital energy demand forecasting for prioritisation during periods of constrained supply

Purpose: Sustaining healthcare operations without adequate energy capacity creates significant challenges, especially during periods of constrained energy supply. This research develops a clinical and non-clinical activity-based hospital energy model for electrical load prioritization during periods of constrained energy supply. Design/methodology/approach: Discrete event modelling is adopted for development of the hospital energy model (HEM). The building block of the HEM is business process mapping of a hospitals clinical and non-clinical activities. The model prioritizes the electrical load demand as Priority 1, 2 and 3; Priority 1 activities are essential to the survival of patients, Priority 2 activities are critical activities that are required after one to four hours, and Priority 3 activities can run for several hours without electricity. Findings: The model was applied to small, medium, and large hospitals. The results demonstrate that Priority 2 activities have the highest energy demand, followed by Priority 1 and Priority 3 activities, respectively for all hospital sizes. For the medium and large hospitals, the top three contributors to energy demand are lighting, HVAC, and patient services. For the small hospital, it is patient services, lighting, and HVAC. Research limitations/implications: The model is specific to hospitals but can be modified for other healthcare facilities. Practical implications: The resolution of the electrical energy demand down to the business activity level enables hospitals to evaluate current practices for optimization. It facilitates multiple energy supply scenarios, enabling hospital management to conduct feasibility studies based on available power supply options Social implications: Improved planning of capital expenditure and operational budgets. Improved operations during periods of constrained energy supply, which reduces the risk to hospitals and ensures consistent quality of service. Originality/value: Current hospital energy models are limited, especially for operations management under constrained energy supply. A simple to use model is proposed to assist in planning of activities based on available supplyPeer Reviewe

4IR integration of information technology best practice framework in operational technology

Purpose: Since inception in the 1970s, Operational Technology (OT) systems were designed to operate in isolation from Information Technology (IT) systems mainly due to differences in objectives relating to Confidentiality, Integrity, Security and Availability (CISA). Additional diverse components include computing speed, and failure severity in terms of safety, environmental, and financial impact. With the onset of Industry 4.0 and the need for integration the worlds of IT and OT must operate in unison. The focal point of this research is to evaluate if an Information Technology Service Management (ITSM) best practice framework can be integrated into the operational technology domain. Design/methodology/approach: A qualitative desk research methodology initiates data gathering on the two key domains. A comparative analysis is subsequently adopted for results analysis. Thereafter, an application case of ITSM inclusive of OT is proposed and reviewed. Findings: After comparative analysis and application case, the research concludes that an IT best practice framework i.e. the Information Technology Infrastructure Library (ITIL) can be integrated and adapted into the operational technology domain to facilitate management of OT in a service management style. Practical implications: The key benefit of this work is the inclusion of OT in global IT best practices in this Fourth Industrial Revolution (4IR) era. Originality/value: This paper contributes to ongoing research in IT-OT integration by providing a unique perspective on OT management in the Fourth Industrial Revolution (4IR). Other researchers can utilize the research outcomes to apply ITSM in the OT domain where 4IR technologies have been implemented

Greenwashing, Sustainability Reporting, and Artificial Intelligence: A Systematic Literature Review

The rise of stakeholder interest globally in sustainable business practices has resulted in a rise in demands from stakeholders that companies report on the environmental and social impacts of their business activities. In certain cases, however, companies have resorted to the practice of providing inaccurate disclosures regarding sustainability as part of their corporate communications and sustainability reporting—commonly referred to as “greenwashing”. Concurrently, technological improvements in artificial intelligence have presented the means to rapidly and accurately analyze large volumes of text-based information, such as that contained in sustainability reports. Despite the possible impacts of artificial intelligence and machine learning on the fields of greenwashing and sustainability reporting, no literature to date has comprehensively and holistically addressed the interrelationship between these three important topics. This paper contributes to the body of knowledge by using bibliometric and thematic analyses to systematically analyze the interrelationship between those fields. The analysis is also used to conjecture a conceptual and thematic framework for the use of artificial intelligence with machine learning in relation to greenwashing and company sustainability reporting. This paper finds that the use of artificial intelligence in relation to greenwashing, and greenwashing within sustainability reporting, is an underexplored research field

Cómo la transformación digital puede permitir a las PYMEs alcanzar el desarrollo sostenible: Una revisión sistemática

[ENG] Small and medium-sized enterprises (SMEs) are key drivers of economic growth and development. Innovation through digital transformation has the capacity to enable sustainability, competitiveness and customisation in products and services. However, adoption of digital technologies by SMEs to underpin sustainability outcomes is poorly understood. A systematic literature review identified an initial dataset of 1300 articles, which after screening and application of exclusion criteria resulted in a dataset of 64 articles for synthesis. Analysis was carried out according to three main areas, namely the technology aspects of digital transformation, sustainable development according to the triple bottom line (i.e. economic, environmental and social aspects), and the business characteristics of SMEs. In the latter case, business strategy and management, organizational structure, organizational culture, skills and qualifications, and leadership factors are identified from the literature. Furthermore, literature expressing the triple bottom line dimensions and the type of Industry 4.0 technology areas adopted are synthesized. Correlation of the data through bibliographic analysis is provided on the type of technology enabling SMEs towards a pathway for sustainable development as well as synthesis of future research directions arising from the study. [SPA] Las pequeñas y medianas empresas (PYMEs) son motores clave del crecimiento y desarrollo económico. La innovación a través de la transformación digital tiene la capacidad de permitir la sostenibilidad, la competitividad y la personalización de los productos y servicios. Sin embargo, la adopción de tecnologías digitales por parte de las PYMES para apuntalar los resultados de sostenibilidad es poco conocida. Una revisión bibliográfica sistemática identificó un conjunto de datos inicial de 1.300 artículos, que tras el cribado y la aplicación de criterios de exclusión dio como resultado un conjunto de 64 artículos para sintetizar. El análisis se llevó a cabo en tres áreas principales, a saber, los aspectos tecnológicos de la transformación digital, el desarrollo sostenible según la triple cuenta de resultados (es decir, los aspectos económicos, medioambientales y sociales) y las características empresariales de las PYMEs. En este último caso, se identifican a partir de la literatura la estrategia y la gestión empresarial, la estructura organizativa, la cultura organizativa, las competencias y las cualificaciones, y los factores de liderazgo. Además, se sintetiza la literatura que expresa las dimensiones de la triple cuenta de resultados y el tipo de áreas tecnológicas de la Industria 4.0 adoptadas. Se ofrece una correlación de los datos a través del análisis bibliográfico sobre el tipo de tecnología que permite a las PYMEs avanzar hacia una vía de desarrollo sostenible, así como una síntesis de las futuras direcciones de investigación que surgen del estudio

Optimising Maintenance Workflows in Healthcare Facilities: A Multi-Scenario Discrete Event Simulation and Simulation Annealing Approach

Healthcare systems in low-resource settings need effective methods for managing their scant resources, especially people and equipment. Digital technologies may provide means for circumventing the constraints hindering low-income economies from improving their healthcare services. Although analytical and simulation techniques, such as queuing theory and discrete event simulation, have already been successfully applied in addressing various optimisation problems across different operational contexts, the literature reveals that their application in optimisation of healthcare maintenance systems remains relatively unexplored. This study considers the problem of maintenance workflow optimisation with respect to labour, equipment availability and cost. The study aims to provide objective means for forecasting resource demand, given a set of task requests with varying priorities and queue characteristics that flow from multiple queues, and in parallel, into the same maintenance process for resolution. The paper presents how discrete event simulation is adopted in combination with simulated annealing to develop a decision-support tool that helps healthcare asset managers leverage operational performance data to project future asset-performance trends objectively, and thereby determine appropriate interventions for optimal performance. The study demonstrates that healthcare facilities can achieve efficiency in a cost-effective manner through tool-generated maintenance strategies, and that any future changes can be expeditiously re-evaluated and addressed