Balancing Demand and Supply in Complex Manufacturing Operations: Tactical-Level Planning Processes

By balancing medium-term demand and supply, tactical planning enables manufacturing firms to realize strategic, long-term business objectives. However, such balancing in engineer-to-order (ETO) and configured-to-order (CTO) operations, due to the constant pressure of substantial complexity (e.g., volatility, uncertainty, and ambiguity), induces frequent swings between over- and undercapacity and thus considerable financial losses. Manufacturers respond to such complexity by using planning processes that address the business’s needs and risks at various medium-term horizons, ranging from 3 months to 3 years. Because the importance of decision-making increases exponentially as the horizon shrinks, understanding the interaction between complexity and demand-supply balancing requires extending findings reported in the literature on operations and supply chain planning and control. Therefore, this thesis addresses complexity’s impact on planning medium-term demand-supply balancing on three horizons: the strategic– tactical interface, the tactical level, and the tactical–operational interface.To explore complexity’s impact on demand–supply balancing in planning processes, the thesis draws on five studies, the first two of which addressed customer order fulfillment in ETO operations. Whereas Study I, an in-depth single-case study, examined relevant tactical-level decisions, planning activities, and their interface with the complexity affecting demand–supply balancing at the strategic–tactical interface, Study II, an in-depth multiple-case study, revealed the cross-functional mechanisms of integration affecting those decisions and activities and their impact on complexity. Next, Study III, also an in-depth multiple-case study, investigated areas of uncertainty, information-processing needs (IPNs), and information-processing mechanisms (IPMs) within sales and operations planning in ETO operations. By contrast, Studies IV and V addressed material delivery schedules (MDSs) in CTO operations; whereas Study IV, another in-depth multiple-case study, identified complexity interactions causing MDS instability at the tactical–operational interface, Study V, a case study, quantitatively explained how several factors affect MDS instability.Compiling six papers based on those five studies, the thesis contributes to theory and practice by extending knowledge about relationships between complexity and demand–supply balancing within a medium-term horizon. Its theoretical contributions, in building upon and supporting the limited knowledge on tactical planning in complex manufacturing operations, consist of a detailed tactical-level planning framework, identifying IPNs generated by uncertainty, pinpointing causal and moderating factors of MDS instability, and balancing complexity-reducing and complexity-absorbing strategies, cross-functional integrative mechanisms, IPMs, and dimensions of planning process quality. Meanwhile, its practical contributions consist of concise yet holistic descriptions of relationships between complexity in context and in demand– supply balancing. Manufacturers can readily capitalize on those descriptions to develop and implement context-appropriate tactical-level planning processes that enable efficient, informed, and effective decision-making

Self-supervised learning methods and applications in medical imaging analysis: A survey

The scarcity of high-quality annotated medical imaging datasets is a major problem that collides with machine learning applications in the field of medical imaging analysis and impedes its advancement. Self-supervised learning is a recent training paradigm that enables learning robust representations without the need for human annotation which can be considered an effective solution for the scarcity of annotated medical data. This article reviews the state-of-the-art research directions in self-supervised learning approaches for image data with a concentration on their applications in the field of medical imaging analysis. The article covers a set of the most recent self-supervised learning methods from the computer vision field as they are applicable to the medical imaging analysis and categorize them as predictive, generative, and contrastive approaches. Moreover, the article covers 40 of the most recent research papers in the field of self-supervised learning in medical imaging analysis aiming at shedding the light on the recent innovation in the field. Finally, the article concludes with possible future research directions in the field

Managing complexity through integrative tactical planning in engineer-to-order environments: insights from four case studies

Fulfilling customer orders in engineer-to-order (ETO) settings entails customization and, thus, greater complexity: detail and uncertainty. Tactical planning aims at demand–supply (DS) balancing by ensuring cross-functional integration (CFI), which incorporates coordination as one dimension. This study uses a case study approach to identify the key coordination mechanisms applied in the customer order fulfilment processes (COFPs) to mitigate the negative impact of complexity on DS balancing in four ETO-oriented settings. Within-case analyses identify the applied mechanisms, and a cross-case analysis elaborates on how they influence the detail and uncertainty in decision-making and problem-solving activities. Findings suggest a positive effect of formalized activity sequences, balanced team compositions, effective task designs and supportive information systems (ISs); and a positive (but contingent) effect of the other mechanisms. Future research may address other CFI dimensions (collaboration), statistically test the findings, or qualitatively deepen the understanding of the forms and impacts of individual mechanisms

A Tactical Demand-Supply Planning Framework to manage ‎‎Complexity in Engineer-to-Order Environments: Insights from an in-‎‎depth ‎case study

The challenging demand-supply balancing in engineer-to-order (ETO) environments\ua0is often attributed to complexity. This study expands the understanding of managing\ua0complexity to obtain demand-supply balancing, focusing on the tactical planning\ua0logic of the order fulfilment process. An in-depth single case study was conducted\ua0and data describing the order fulfilment process at a construction company were\ua0collected and analysed. Findings suggest a tactical-level planning process framework,\ua0incorporating nine key decisions and three crucial activities, and their potential\ua0complexity-reducing and complexity-absorbing impact. The study contributes to the\ua0theoretical discussion of complexity in management practices, linking demandsupply\ua0balancing as a performance measure. The findings guide practitioners in ETO\ua0settings on anticipating potential medium-term consequences of key decisions on\ua0capacity. This emphasises the need of proper IT support to apply knowledge\ua0generated from previous projects and conduct comprehensive and robust scenariobased\ua0analyses

Development of Temperature Distribution and Light Propagation Model in Biological Tissue Irradiated by 980 nm Laser Diode and Using COMSOL Simulation

Introduction: The purpose of this project is to develop a mathematical model to investigate light distribution and study effective parameters such as laser power and irradiated time to get the optimal laser dosage to control hyperthermia. This study is expected to have a positive impact and a better simulation on laser treatment planning of biological tissues. Moreover, it may enable us to replace animal tests with the results of a COMSOL predictive model.Methods: We used in this work COMSOL5 model to simulate the light diffusion and bio-heat equation of the mouse tissue when irradiated by 980 nm laser diode and the effect of different parameters (laser power, and irradiated time) on the surrounding tissue of the tumor treatment in order to prevent damage from excess heatResults: The model was applied to study light propagation and several parameters (laser power, irradiated time) and their impact on light-heat distribution within the tumor in the mouse back tissueThe best result is at laser power 0.5 W and time irradiation 0.5 seconds in order to get the maximum temperature hyperthermia at 52°C.Conclusion: The goal of this study is to simulate a mouse model to control excess heating of tissue and reduce the number of animals in experimental research to get the best laser parameters that was safe for use in living animals and in human subjects

A Modelling approach for evaluating the ranking capability of Situational Awareness System in real time operation. Modelling, evaluating and quantifying different situational assessment in real time operation, using an analytical approach for measuring the ranking capability of SWA system

In a dynamically monitored environment the analyst team need timely and accurate information to conduct proactive action over complex situations. Typically, there are thousands of reported activities in a real time operation, therefore steps are taken to direct the analyst’s attention to the most important activity. The data fusion community have introduced the information fusion model, with multiple situational assessments. Each process lends itself to ranking the most important activities into a predetermined order. Unfortunately, the capability of a real time system can be hindered by the knowledge limitation problem, particularly when the underlying system is processing multiple sensor information. Consequently, the situational awareness domains may not rank the identified situation as perfect, as desired by the decision-making resources. This thesis presents advanced research carried out to evaluate the ranking capability of information from the situational awareness domains: perception, comprehension and projection. The Ranking Capability Score (RCS) has been designed for evaluating the prioritisation process. The enhanced (RCS) has been designed for addressing the knowledge representation problem in the user system relation under a situational assessment where the proposed number of tracking activities are dynamically shifted. Finally, the Scheduling Capability Score was designed for evaluating the scheduling capability of the situational awareness system. The proposed performance metrics have been successful in fulfilling their objectives. Furthermore, they have been validated and evaluated using an analytical approach, through conducting a rigorous analysis of the prioritisation and scheduling processes, despite any constraints related to a domain-specific configuration

Simulation and Study of Temperature Distribution in Living Biological Tissues under Laser Irradiation

Introduction: With the rapid increase in use of lasers in medical treatments, it is important to understand the mechanisms of heat transfer in biological tissues in order to minimize damage to the tissues resulting from extra heat applied. The aim of this study is to investigate the temperature distribution in living biological tissues when laser irradiation is used in a treatment.Methods:  In this work a model was suggested to study the impact of several parameters such as (laser power, exposure time, laser spot size) on the temperature distribution within skin tissues when subjected to a laser source. A three-dimensional finite element thermal model of biological tissues was developed using bio-heat equation to describe heat transfer in living tissues.Results: Temperature distribution within skin tissues subjected to laser heating is calculated in details using the Finite element method and a suggested model; the results are presented in figures and tables showing the effects of Laser spot size, power and exposure time on temperature distribution within treated tissue.Conclusion: the results presented in this work  are expected to be useful in optimizing Laser spot size, power and exposure time for a variety of laser applications medicine and surgery.   

Blood tumor prediction using data mining techniques

Healthcare systems generate a huge data collected from medical tests. Data mining is the computing process of discovering patterns in large data sets such as medical examinations. Blood diseases are not an exception; there are many test data can be collected from their patients. In this paper, we applied data mining techniques to discover the relations between blood test characteristics and blood tumor in order to predict the disease in an early stage, which can be used to enhance the curing ability. We conducted experiments in our blood test dataset using three different data mining techniques which are association rules, rule induction and deep learning. The goal of our experiments is to generate models that can distinguish patients with normal blood disease from patients who have blood tumor. We evaluated our results using different metrics applied on real data collected from Gaza European hospital in Palestine. The final results showed that association rules could give us the relationship between blood test characteristics and blood tumor. Also, it demonstrated that deep learning classifiers has the best ability to predict tumor types of blood diseases with an accuracy of 79.45%. Also, rule induction gave us an explanation of rules that describes both tumor in blood and normal hematology

Tactical planning in engineer-to-order environments

Tactical planning is implemented to balance customer demand and supply capacity within a medium-term and to avoid under- and overcapacity. In engineer-to-order (ETO) environments, under- and overcapacity lead firms to incur substantial costs that can easily wipe out profit margins. ETO-oriented markets like the construction and capital goods sectors are massive in terms of investments and have considerable impact on the gross domestic product (GDP) of nations. This makes demand-supply (DS) balancing highly important in ETO contexts.The purpose of the thesis is to expand the knowledge about how tactical planning contributes to balancing customer demand and supply capacity in ETO settings. This purpose departed from accepting that – based on extent literature – such knowledge about tactical planning is rather generic and fragmented, which calls for further research. The results in the thesis are presented from literature studies, two single case studies and a multiple case study. Since DS balancing in principle means dealing with the complexity stemming from demand and supply, the thesis results focus on how tactical planning manages such complexity in ETO environments.A single case study, focusing on tactical-level planning activities, together with a multiple case study, focusing on cross-functional integration, address how informal tactical-level planning processes contribute to DS balancing. Including a single case study, focusing on S&OP as a formal tactical-level planning process, the three studies form the empirical base of a framework that responds to the purpose of the thesis. The framework considers complexity, which is represented by two dimensions including detail and uncertainty.The thesis contributes to practical aspects by providing guidance to tactical-level planners in ETO environments concerning the areas of improvement to consider when configuring and upgrading the planning process to manage complexity. The theoretical contribution of the thesis is concerned with the developed framework that describes the relation between tactical planning, DS balancing, cross-functional integration and complexity in ETO settings

MR-derived renal morphology and renal function in patients with atherosclerotic renovascular disease

Appropriate selection of patients with atherosclerotic renovascular disease (ARVD) for revascularization might be improved if accurate non-invasive investigations were used to assess severity of pre-existing parenchymal damage. The purpose of this study was to evaluate the associations between magnetic resonance imaging (MRI)-measured renal morphological parameters and single-kidney glomerular filtration rate (GFR) in ARVD. Three-dimensional (3D)-MRI was performed on 35 ARVD patients. Renal bipolar length (BL), parenchymal volume, parenchymal (PT), and cortical thicknesses (CT) were measured in 65 kidneys. Thirteen kidneys were supplied by normal vessels, 13 had insignificant (<50%) renal artery stenosis (RAS), 33 significant (≥50%) RAS, and six complete vessel occlusion. All patients underwent radioisotopic measurement of single-kidney GFR (isoSK-GFR). Overall, 3D parameters such as parenchymal volume were better correlates of isoSK-GFR (r=0.86, P<0.001) than BL (r=0.78, P<0.001), PT (r=0.63, P<0.001) or CT (r=0.60, P<0.001). Kidneys with ≥50% RAS did show significant reduction in mean CT compared to those supplied by normal vessel (5.67±1.63 vs 7.28±1.80 mm, P=0.002; 22.1% reduction) and an even greater loss of parenchymal volume (120.65±47.15 vs 179.24±86.90 ml, P<0.001; 32.7% reduction) with no significant reduction in BL. In a proportion of ≥50% RAS kidneys, a disproportionately high parenchymal volume to isoSK-GFR was observed supporting a concept of ‘hibernating parenchyma’. 3D parameters of parenchymal volume are stronger correlates of isoSK-GFR than two-dimensional measures of BL, PT or CT. 3D morphological evaluation together with isoSK-GFR might be useful in aiding patient selection for renal revascularization. Kidneys with increased parenchymal volume to SK-GFR might represent a subgroup with the potential to respond beneficially to angioplasty