The aim of this thesis was to locate examples of the active involvement of major food retailers in innovation in food manufacturing, and to explain their reasons for this activity. Two characteristics of the food industry had an important bearing on the research: (1) slow growth in the demand for food and (2) the interaction between increasingly concentrated food manufacturing and retailing industries. The thesis seeks to improve existing theories of innovation, which do not embrace the possibility that retailers may make contributions to innovation in industries from which they obtain their supplies. Two principal investigation techniques were deployed. The first comprised in-depth interviews with major food retailers, which provided data on their purchasing policy for own label products, and on their technological activities. The second assessed the results of these policies by identifying the responsibility for major innovations in chickenmeat processing: a technological history was compiled from data drawn from several sources including industry experts and a literature search. Further studies indicate that the findings from the chickenmeat study are not a special case. The thesis contributes to theories of innovation by showing that food retailers with substantial in-house technological capability have played important roles in influencing technological change in food manufacturing. The need for restraint on the purchasing power of large retailers is an important policy issue. This thesis makes a contribution to the debate. Retailers' procurement policies which have been successful in stimulating innovation may also have wider relevance to other sectors of industry.

Demonstrating compliance with food safety requirements of the global economy is a prerequisite for access. As tariff barriers diminish, developing countries are exposed to greater opportunities for repositioning their food manufacturing sectors in global value chains (GVCs). At the same time, the measures for the protection of public health and safety are becoming more stringent because of the series of food safety crises that characterised the global food value chain in the 1980s and 1990s, and that still linger on. The new demands arising from the need to protect consumer safety, coupled with the structure of the global economy have introduced new challenges for developing countries in terms of accessing the global food manufacturing value chain(GFMVC) with manufactured products. This is the case for the Ghanaian food manufacturing sector. Therefore, this study aims to understand the practice of developing food safety capability to enhance access to the GFMVC using high value added products, to identify performance gaps in the Ghanaian context and propose an appropriate framework (legal, institutional and policy) to address the major gaps, while meeting the basic requirements of food safety. A multiple case study methodology was adopted, using the UK food and drinks sector as a benchmark for the Ghanaian food manufacturing sector. The main techniques employed for data collection were surveys, interviews and content analysis. Based on the findings and insights gathered from the investigation, a technical regulation based on Hazard Analysis and Critical Control Point (HACCP) is proposed as a means to enhance the compliance of enterprises in Ghana with the basic requirements of food safety. Because of the current lack of capability at the national and enterprise level, a four-phase implementation plan is recommended to progressively ease enterprises into mandatory compliance with integrated food safety management systems. The study also recommends that the current multiple agency structure is maintained, however, mandates, roles and responsibilities, and jurisdictions need to be clarified, and values reformed. Various kinds of support (e.g. funds, training) also have to be provided to enterprises to facilitate their compliance and enhance their access to the GFMVC.

Thermal environment control of chilled food manufacturing facilities plays a critical role in maintaining the required food product temperature during processing to ensure food quality and maximise shelf life. The provision of cooling to maintain the required temperatures in the processing halls, which should be in the range between 4 °C and 12°C also impacts on energy consumption and CO2 emissions. Chilled food manufacturing facilities normally have high ceilings to provide flexibility in their use and accommodate different height equipment. In these facilities cooling is commonly provided by fan coil units installed at ceiling level that recirculate air in the space through the cooling coils with high velocities. Small amounts of fresh air can also be provided to the space through a separate fresh air system. The low temperatures and high velocity of air circulating in the space lead to uncomfortable environments for the workers and high energy consumption. Refrigeration systems in chilled food manufacturing facilities account for more than 60% of the energy consumption in the plant so identifying ways of improving the thermal environment in these facilities and reducing energy consumption can lead to increased productivity and profitability of chilled food operations. This thesis makes a contribution to this challenge by investigating alternative air distribution approaches for both existing and new facilities. A primary consideration was to identify solutions that could be easily retrofitted to existing cooling systems in the space at low cost and minimum disruption to the production. The research involved the investigation of two chilled food manufacturing spaces with different cooling system arrangements to establish their performance characteristics and ability to provide the required conditions of temperature and velocities at low level in the space to minimise thermal discomfort. Learnings from these investigations were used to develop in the laboratory a test facility that could reproduce chilled food manufacturing environments at a smaller scale and enable the investigation of different cooling systems and air distribution arrangements. CFD models were also developed and validated against temperature and air velocity data from the chilled food spaces in the factories and the test facility. The models were then used to evaluate different chilled air distribution designs prior to them being manufactured and installed for evaluation in the test facility. The main objective was to achieve temperature stratification and low air velocities at low levels in the space. Key findings and contribution to knowledge for science and technology of cold processing areas are the follow: i) The monitoring of the two case studies provided evidence of the air-temperature distribution issues in existing chilled food facilities such as high velocities, poor temperature distribution, cooling of the whole space and increased energy consumption. ii) Numerical and experimental results of this research provided guidelines of how air distribution solutions in existing chilled food facilities can be improved regarding their air temperature efficacy and energy efficiency. For example, supplying air from evaporator coils at medium level with circular or semi-circular fabric ducts as air distribution solutions, could achieve temperature stratification in the space with lower temperatures at low level covering the manufacturing area and higher temperatures towards the ceiling; In addition, medium level air supply with fabric duct was shown to provide in the region of 9% reduction in energy consumption compared to high level supply with the same duct; Furthermore, medium level air supply with a fabric duct provided 23% energy savings compared to air supply with an un-ducted fan-coil system which is the most common air distribution method in chilled food factories; iii) Numerical and experimental results derived guidelines of which air distribution systems should be avoided in new chilled food facilities. Tests and CFD modelling comparing air distribution with circular fabric duct and metal duct with linear diffusers showed that the circular fabric duct provided a better thermal environment in terms of temperature uniformity and low air velocities; Furthermore, comparing the air flow velocities obtained from the air distribution system via non-ducted coil and fabric ducts as air distribution solutions, it can be highlighted that the fabric duct provided much lower air flow velocities. This is beneficial to achieve some temperature stratification in the space and reduce the discomfort of the workers produced by high velocities as seen in the case of the non-ducted coil. iv) A simulation tool developed that couples refrigeration system and CFD modelling has been shown to be able to simulate the dynamics of air distribution and refrigeration system energy consumption in chilled food spaces. The tool can be used to optimise the design of air distribution systems from both thermal environment and energy consumption perspectives.

Neural networks have become very important tools in many areas including economic researches. The objectives of this thesis are to examine the fundamental components, concepts and theory of neural network methods from econometric and statistic perspective, with particular focus on econometrically and statistically relevant models. In order to evaluate the relative effectiveness of econometric and neural network methods, two empirical studies are conducted by applying neural network methods in a methodological comparison fashion with traditional econometric models.Both neural networks and econometrics have similar models, common problems of modeling and interference. Neural networks and econometrics/statistics, particularly their discriminant methods, are two sides of the same coin in terms of the nature of modeling statistic issues. On one side, econometric models are sampling paradigm oriented methods, which estimate the distribution of the predictor variable separately for each class and combine these with the prior probabilities of each class occurring; while neural networks are one of the techniques based on diagnostic paradigm, which use theinformation from the samples to estimate the conditional probability of an observation belonging to each class, based on predictor variables. Hence, neural network and econometric/statistical methods (particularly, discriminant models) have the same properties, except that the natural parameterizations differ.The empirical studies indicate that neural network methods outperform or are as good as traditional econometric models including Multiple Regression Analysis, Linear Probability Model (LPM), and Logit model, in terms of minimizing the errors of in-sample predictions and out-of-sample forecasts. Although neural networks have some advantages over econometric methods, they have some limitations too. Hence, neural networks are perhaps best viewed as supplements to econometric methods in studying economic issues, and not necessarily as substitutes.

This thesis presents research undertaken to understand and enhance resilience in the UK Food and Drink Manufacturing Sector. It focuses on the development of a conceptual framework which establishes how specific vulnerabilities link to individual mitigation strategies available to the sector and the impact of such strategies on wider sustainability. The research in this thesis is divided into four main parts. The first part consists of three complementary review chapters exploring resilience as a theoretical concept, resilience in the UK Food and Drink Manufacturing sector and existing methods used to study and/or enhance resilience. The second part of the thesis begins by describing how the pragmatic philosophy and abductive stance underpinning the research, in combination with review findings, helped to determine the research techniques used in this work, which included the systematic review process and the mixed methods case study. Next, the research facilitating a novel conceptual framework describing how real-time vulnerabilities can be identified and mitigated in a way that is complimentary to the wider sustainability of the organisation is discussed. The third part of the thesis describes the practical set of tools, presented in the form of a workbook, which enable a Food and Drink Manufacturer to utilise the conceptual framework teachings to enhance their own resilience. The final section details key conclusions regarding the conceptual nature and practical enhancement of resilience for Food and Drink Manufacturers and the wider food system, as well as opportunities for future work. The conceptual integrity and practical usefulness of the conceptual framework and its derivative workbook toolset have been demonstrated through case studies with two UK Food and Drink Manufacturers. Results suggest two major benefits of the framework are the ability to identify an organisation's vulnerabilities based on actual mapping of their supply network and the ability to evaluate mitigating resilience strategies based on their broader impacts elsewhere within the organisation. In summary, the research reported in this thesis has concluded that resilience cannot be seen as a one-off solution for returning to how things were before disruption, but instead is a constant process of learning and adaptation in response to a company's ever-changing operating environments. The framework and workbook presented provide a novel and practical method for UK Food and Drink Manufacturers, of all sizes and production ranges, to identify and respond to their evolving vulnerabilities, as well as providing much needed synthesis and directions for future work at an academic level.

The purpose of this research was to determine if bacteriophage (phage) could be used to treat and reduce the incidence of Listeria in food manufacturing facilities, and thereby reduce the risk of food products being cross-contaminated with Listeria monocytogenes. Listeria incidence in food manufacturing ready-to-eat environments was surveyed at 31 ready-to-eat (RTE) food plants. A total 4,829 samples were collected from all locations. Nine (29%) facilities had zero samples positive for Listeria spp., whereas 22 (71%) had one or more samples positive. The total incidence of Listeria spp. in all RTE food plants was 4.5%. The effectiveness of phage against Listeria was determined when applied to stainless steel, polyurethane thermoplastic, and epoxy. Each material was inoculated with a cocktail containing L. monocytogenes and L. innocua (4 to 5-log10 CFU/cm2) and treated with two different concentrations of phage (2x10^7 and 1x10^8 PFU/cm2). Treated samples were held at 4 or 20°C for 1 and 3h. After treatment with phage, Listeria reductions ranged from 1.27–3.33 log10 CFU/cm2 on stainless steel, 1.17–2.76 log10 CFU/cm2 on polyurethane thermoplastic, and 1.19–1.76 log10 CFU/cm2 on epoxy. Listeria reduction occurred on all materials tested, under all conditions. Higher phage concentration, longer time, and higher environmental temperatures led to significantly (P<0.05) greater reduction of Listeria on stainless-steel and polyurethane thermoplastic. The effectiveness of a phage against Listeria spp. was evaluated in two food manufacturing facilities, operating at either 4°C or 20°C. First, a moderate application of a 2x10^7 PFU/mL phage was applied once per day over three days and samples were collected and analyzed for Listeria at 0, 24, 48 and 72 h. This phage treatment led to a decrease in the incidence of Listeria by 67%. A second application method was studied with phage being applied in the food manufacturing environment in an intensified manner (3 times in 18 hours) at a higher concentration of phage (1x10^8 pfu/mL). This intensified application led to a 32% overall reduction in the incidence of Listeria in the production environment. Applications of Listeria specific phage can be an additional intervention strategy for controlling pathogenic Listeria organisms in food production facilities. / Doctor of Philosophy / Listeriosis is a serious illness caused by the bacterium Listeria monocytogenes. Annually in the United States it is estimated that 95.7% of all listeriosis illnesses are caused by the consumption of contaminated food, and it is generally recognized that L. monocytogenes is caused by cross contamination of ready-to-eat foods from an environmental source. The purpose of this research was to determine if food manufacturing facilities could use bacteriophage (phage) to treat and reduce the incidence of Listeria in food manufacturing plant, and thereby reduce the risk of food products being cross-contaminated with L. monocytogenes. The incident rate of Listeria was surveyed by collecting 4,829 samples from 31 ready-to-eat (RTE) food plants across the United States. Nine (29%) facilities had zero samples positive for Listeria spp., whereas 22 (71%) plants had one or more samples positive. The total incidence of Listeria spp. in all RTE food plant samples was 4.5%. Second, research was completed to determine if phage at different levels reduced Listeria on three common food manufacturing plant materials (stainless steel, polyurethane belting and epoxy flooring). After Listeria was attached to each material (4 to 5-log10 CFU/cm2), they were treated with two different levels of phage (2x10^7 and 1x10^8 PFU/cm2) at two temperatures (4 or 20°C) for 1 and 3 hours. After treatment with phage, Listeria reduction of 93.2 to 99.9% occurred on all materials tested, under all conditions. Finally, two different methods of applying phage (moderate and intensified) in a food manufacturing plant was studied. The moderate application was a single treatment with lower concentration of phage (2x10^7 PFU/mL) once per day for three days, while the intensified treatment was the application of high phage concentrations (1x10^8 pfu/mL) three different times, all in a single day. Both application methods reduced the incidence of Listeria in the food manufacturing plant. The total reduction across all trials was 67% using the moderate application method and 32% using the intensified application of phage.

Since the realisation of the computer, and shortly after the inception of artificial intelligence (AI), there has been an explosion of research solving human-level tasks using autonomous entities that are able to learn about an environment by observing and influencing it, known as intelligent agents (IA). This potent AI technique has yet to filter into the field of thermoscience, where the conceptual design and optimisation of complex energy systems has been a particularly challenging problem. Much of the design process still requires human expertise. But with the continual increase in computational power and the use of IAs, it is now time to shift the responsibility from the human to the computer. This research attempts to answer the question of whether it is possible for a computer to conceptually design a complex energy system autonomously, from inception. The complex energy system to be designed and optimised is a thermoacoustic heat engine (TAHE), which converts thermal to acoustic power. The complexity of its physical behaviour and its many design parameters makes it a challenging energy system for conceptual design and optimisation and consequently an ideal candidate for this particular research. The TAHE is designed for low temperature waste heat utilisation from a baking process. In this work an approach is employed that is based on a reinforcement learning intelligent agent (RLIA). The RLIA is first employed to simultaneously optimise thirteen design parameter values. The RLIA was able to learn key design features of a TAHE which lead to the reduction in acoustic losses and an acoustic power from the engine of 495.32 W, when the thermal power input was 19 kW. For the main experiment, the RLIA must conceptually design the TAHE from scratch, changing both the parameter values and the configuration of the device. The results have shown the remarkable ability of the RLIA to identify several key design features of the TAHE: the correct configuration of the device, selecting designs that reduce acoustic losses, create positive acoustic power in the stack region and determine the region of optimality of the design parameter values. The RLIA has shown a great capacity to learn, even when contending with a complex environment and a vast search space. With this work we have introduced RLIAs as a new way approach to such multidimensional problems in the field of thermoscience/thermal engineering.

This study addresses the importance of cost accounting and performance evaluation for organizations. Further, this study explains the purposes of cost accounting and performance evaluation. The chosen method is a single case study which investigates how product costing is made within a food manufacturing company, called Omega in this study. Interviews have been an important tool for collecting data; data used to create a snapshot of Omega’s current operations. Cost concepts, cost allocation methods, and performance evaluation theories are presented and later compared with the snapshot of Omega. Dissatisfaction concerning product costing in Omega was first expressed by a business unit manager. Search revealed that the issue concerning product costing was not a problem per se; instead it was a symptom of a more fundamental issue. The more fundamental issue is Omega’s cost accounting and financial performance evaluation used throughout the organization. Omega evaluates its business units using financial operating results measures based on information from its cost accounting system. Uncertainty within Omega has been observed concerning a performance measure called operational result. Search has revealed that the business units within Omega do not have the ability to control costs upon which they are evaluated, and further that all costs are not relevant for business unit performance evaluation. Three cost categories for cost accounting have been constructed with the purpose of serving as a base for financial performance evaluation. Treating costs differently based upon their characteristics enables organizations to form a well-functioning financial performance evaluation system which can lead the organization in the right direction. Ultimately, a well-functioning financial performance evaluation system enhances motivation and commitment in business units as well as it gives the top management a correct performance indicator.

ivABSTRACTBusinesses must overcome a variety of difficulties as a result of the considerable changersin the global economy. Due to import limitations, excessive inflation, and ongoing foreignexchange troubles in the economy. Sri Lankan industries, particularly food markers, arecurrently experiencing extremely difficult times. For many people in the nation, the foodbusiness is crucial. A nation’s ability to succeed economically and politically depends onthe availability of cheap, nutritious food that is also in good supply. The government isaware that consumers care about the cost and safety of the food they eat. Everyone alsoseems to be becoming more concerned about the origin of their food, how it is raised orcultivated, and whether it is sufficiently nutrient-dense. The food sector is tightly regulatedto ensure everything runs smoothly due to the necessity to supply food safety and value. Inmost sectors, of the company's inventory makes up a sizeable portion of its current assets.It's beneficial for the business process to manage such inventories in order to prevent lossesbrought on by stock shortfalls and surpluses. There were several examples where companieswere collapsed due to mismanagement of their inventories. Thus, this research expected toexamine the impact of inventory management on profitability of listed food manufacturingcompanies in Sri Lanka as this sector operation is highly relied on the inventories.A quantitative research strategy was adopted for this study and financial data was obtainedfrom the published annual reports of 14 listed food manufacturing companies on theColombo Stock Exchange for a period of 5 years from 2016/2017 to 2020/2021 to conductthe analysis. In this regard descriptive, correlation and regression analysis were conductedto analyze the data by using Statistical package for the social science (SPSS) software.Inventory turnover, number of inventory days and gross margin return on inventory havebeen identified as dimensions to measure the independent variable of inventorymanagement. Company profitability has been identified as the dependent variable and itwas measured through return on equity and return on assets. Six hypotheses wereestablished and tested to ascertain how inventory management affects profitability based onthese five variables. Results of the study show that inventory turnover has a significantnegative impact on return on assets and medium negative impact on return on equity. Thestudy also reveals that the number of inventory days and gross margin return on inventoryhas no significant impact on return on assets and return on equity. The study's findings willbe crucial in advising policy makers, operational managers of food manufacturingcompanies for the efficient inventory management which lead to enhance the profitabilityof those companies.

Yes / Today’s factories are considered as smart ecosystems with humans, machines and devices interacting with each other for efficient manufacturing of products. Industry 4.0 is a suite of enabler technologies for such smart ecosystems that allow transformation of industrial processes. When implemented, Industry 4.0 technologies have a huge impact on efficiency, productivity and profitability of businesses. The adoption and implementation of Industry 4.0, however, require to overcome a number of practical challenges, in most cases, due to the lack of modernisation and automation in place with traditional manufacturers. This paper presents a first of its kind case study for moving a traditional food manufacturer, still using the machinery more than one hundred years old, a common occurrence for small- and medium-sized businesses, to adopt the Industry 4.0 technologies. The paper reports the challenges we have encountered during the transformation process and in the development stage. The paper also presents a smart production control system that we have developed by utilising AI, machine learning, Internet of things, big data analytics, cyber-physical systems and cloud computing technologies. The system provides novel data collection, information extraction and intelligent monitoring services, enabling improved efficiency and consistency as well as reduced operational cost. The platform has been developed in real-world settings offered by an Innovate UK-funded project and has been integrated into the company’s existing production facilities. In this way, the company has not been required to replace old machinery outright, but rather adapted the existing machinery to an entirely new way of operating. The proposed approach and the lessons outlined can benefit similar food manufacturing industries and other SME industries. / Innovate UK—Knowledge Transfer Partnerships (KTP010551)