Application of the agile energy model to the procure to pay process

Abstract: Multinational Manufacturing Corporations (MMC’s), which account for a fair percentage of the manufacturing industry encounter challenges with energy quantification and optimisation. Traditional energy models, which have long been used for energy system evaluations have limited application at MMC’s due to model characteristics of high level of expertise, data and time intensive, long time horizons and large spatial detail. The Agile Energy Model utilises business processes for energy evaluation and optimisation. The features of the Agile Energy Model supporting application at MMC’s are generic, reproducible, ease of use, minimum user input data and time requirements and transparency of the evaluation process. It enables the energy quantification of non-traditional activities of finance, HR, ICT and sales and marketing. The methodology of application of the Agile Energy Model is demonstrated with the established procure to pay process

Agile energy modelling : a business centric approach

Abstract: Energy management is a crucial aspect to global sustainability. Multinational Manufacturing Corporations’ (MMC’s) utilise a large amount of energy, making energy optimisation a priority. The ability to evaluate MMC’s total energy utilisation effectively and efficiently is a challenge. This research focuses on holistically modelling the business energy systems of MMC’s by adopting a business process centric approach. MMC’s conduct business based on global or regional business processes depending on the function, global/regional functional enablement. The agile energy model proposed in this research integrates key knowledge areas of energy assessment, business management, business processes and system engineering, to deliver a comprehensive simulation toolset for energy quantification, evaluation and optimisation

Industry 4.0 Technological Advancement in the Food and Beverage Manufacturing Industry in South Africa—Bibliometric Analysis via Natural Language Processing

The food and beverage (FOODBEV) manufacturing industry is a significant contributor to global economic development, but it is also subject to major global competition. Manufacturing technology evolution is rapid and, with the Fourth Industrial Revolution (4IR), ever accelerating. Thus, the ability of companies to review and identify appropriate, beneficial technologies and forecast the skills required is a challenge. 4IR technologies, as a collection of tools to assist technological advancement in the manufacturing sector, are essential. The vast and diverse global technology knowledge base, together with the complexities associated with screening in technologies and the lack of appropriate enablement skills, makes technology selection and implementation a challenge. This challenge is premised on the knowledge that there are vast amounts of information available on various research databases and web search engines; however, the extraction of specific and relevant information is time-intensive. Whilst existing techniques such as conventional bibliometric analysis are available, there is a need for dynamic approaches that optimise the ability to acquire the relevant information or knowledge within a short period with minimum effort. This research study adopts smart knowledge management together with artificial intelligence (AI) for knowledge extraction, classification, and adoption. This research defines 18 FOODBEV manufacturing processes and adopts a two-tier Natural Language Processing (NLP) protocol to identify technological substitution for process optimisation and the associated skills required in the FOODBEV manufacturing sector in South Africa

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

A comparative analysis of the postural and diurnal ocular perfusion pressure of young healthy individuals of different ethnicities

Purpose: Ocular perfusion pressure (OPP) regulates the flow of blood to the optic nerve and is determined by the interaction between intraocular pressure (IOP) and blood pressure (BP). Low OPP increases the incidence of primary open-angle glaucoma (POAG). The aim is to compare the diurnal (i.e. morning vs. afternoon) and postural (i.e. seated vs. supine) OPP in healthy individuals from different ethnicities aged between 18 and 30 years. Methodology: Averaged IOP and BP measurements were obtained with an ICare rebound tonometer and an automated sphygmomanometer, respectively. Measurements were taken in the morning and afternoon, in the supine and seated positions in healthy young adults: Africans (n = 10), white people (n = 10), mixed-race people (n = 10) and Indians (n = 10). Results: The whole sample (N = 40) displayed a statistically significant reduction in postural and diurnal OPP both in the supine position and in the morning, respectively. A comparative analysis revealed that Africans displayed statistically significant reduction in OPP when compared to other ethnicities. Discussion: A change in posture to the supine position has a greater impact on the reduction of OPP when compared to diurnal changes. Africans displayed clinically significant reduction in OPP which may increase the incidence of POAG in this ethnicity at an early age. Conclusion: Our findings question whether OPP should be considered as a biomarker in the dark-skinned individuals. An evaluation of BP and IOP in the supine position is recommended for all patients to obtain more conclusive readings

Comparative genomics of Cluster O mycobacteriophages

Mycobacteriophages - viruses of mycobacterial hosts - are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages - Corndog, Catdawg, Dylan, Firecracker, and YungJamal - designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange

Evolution of extensively drug-resistant tuberculosis over four decades: whole genome sequencing and dating analysis of Mycobacterium tuberculosis isolates from KwaZulu-Natal.

CAPRISA, 2015.Abstract available in pdf

Genomic and functional analyses of mycobacterium tuberculosis strains implicate ald in D-cycloserine resistance.

CAPRISA, 2016.Abstract available in PDF file

Digital Platforms for SMME Enablement

The challenges facing SMME's are diverse ranging from skills challenges to value chain optimization, concept management and operations management. The entrepreneur navigates a typical SMME cycle from idea generation to sustainable business single-handed. Each phase of SMME development is a challenge but is not unique to the individual SMME. Financial management, marketing, logistics, people management and general strategy to execution against challenges are endured and overcome by SMME's. SMME’s form the majority of businesses, in most economies and is a source of GDP growth. SMME failure rates are high across the globe with significant challenges to survive. Innovation centers, incubation models and various other interventions have impacted SMME survival but more should be done. The research presented in this paper revolves around a theoretical digital platform for SMME sustainability. The platform is evolutionary and based on large corporate processes and systems, subdued and modified for SMME support. Core SMME processes are digitalized and provide for a single strategy. The evolutionary platform builds over time and evolves to an intuitive digital SMME support system. An initial literature analysis leading onto a theoretical SMME framework and systems dynamics model is presented