{"title":"Strategic and tactical planning model for the design of perishable product supply chain network in Ethiopia","authors":"Asnakech Biza , Ludovic Montastruc , Stéphane Negny , Shimelis Admassu","doi":"10.1016/j.compchemeng.2024.108814","DOIUrl":"10.1016/j.compchemeng.2024.108814","url":null,"abstract":"<div><p>This article discusses the challenges associated with ensuring food security for a growing global population and emphasizes the critical role of the Agri Fresh Food Supply Chain in addressing these challenges such as mitigating food insecurity and reducing wastes. The economic repercussions of inefficiencies in perishable supply chains impact businesses' profit margins and consumers' access to essential goods. The focus is on the effective management of the complex perishable product supply chains, considering the economic significance of this sector and the need for advanced strategies to optimize the flow of time-sensitive products. The study discusses the limited consideration of product intrinsic characteristics in strategic and tactical planning decisions. The research aims to contribute to supply chain management by proposing a mathematical model (multi echelon, multi product, and multi period) for designing a perishable product supply chain network, considering factors like perishability, quantity discount policy, souring strategies and business continuity. The study explores the impact of these factors on the Agri Fresh Food Supply Chain design and its overall performances. Although the proposed model is designed to be applicable to any country or region, but its capabilities are shown through a real case study in Ethiopia. Results show that a agri-food supply chain design model that considers the intrinsic characteristics of the product, processing capacity level, and quantity discount leads to improved configurations of the food supply chain regardless of adding the associated cost.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"190 ","pages":"Article 108814"},"PeriodicalIF":3.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141998015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Zonewise surrogate-based optimization of box-constrained systems","authors":"Srikar Venkataraman Srinivas, Iftekhar A. Karimi","doi":"10.1016/j.compchemeng.2024.108821","DOIUrl":"10.1016/j.compchemeng.2024.108821","url":null,"abstract":"<div><p>Complex physical or numerical systems may exhibit distinct behaviors in various zones of their design spaces. We present an algorithm that uses multiple cluster-based surrogates for optimizing such box-constrained systems. It partitions the design space into multiple clusters using K-means clustering and develops a separate surrogate for each cluster. It then uses these surrogates to sample additional points in the design space whose function evaluations guide the search for a global optimum. Clustering, surrogate construction, and smart sampling are employed iteratively to add sample points until a pre-defined threshold. The best solution from these points estimates a global optimum. An extensive test bed of 52 box-constrained functions was used to evaluate and compare the algorithm's performance and computational requirements with sixteen derivative-free optimization solvers. The best version of our algorithm surpassed all sixteen solvers in optimization accuracy for a fixed number of evaluations and demanded lower computational effort than fifteen.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108821"},"PeriodicalIF":3.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141938878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kozue Okamura, Kota Oishi, Sara Badr, Akira Yamada, Hirokazu Sugiyama
{"title":"Data-driven parameterization and development of mechanistic cell cultivation models in monoclonal antibody production processes: Shifts in cell metabolic behavior","authors":"Kozue Okamura, Kota Oishi, Sara Badr, Akira Yamada, Hirokazu Sugiyama","doi":"10.1016/j.compchemeng.2024.108822","DOIUrl":"10.1016/j.compchemeng.2024.108822","url":null,"abstract":"<div><p>Representative kinetic models to describe monoclonal antibody (mAb) production processes are needed for effective process design. The development of mechanistic models can be impeded by the lack of complete understanding of changes in cell metabolism, e.g., lactate metabolic shifts. State-estimation-based methods were applied to assess the fit of available kinetic models over experimental runs. The results indicated the regions where model parameter updates were required. Different clustering strategies were applied to isolate the variations in the culture environment and correlate them to the lactate shifts. Alternative formulations for the specific lactate consumption/production term were provided for each identified phase. Two case studies are presented for pilot-scale data in different reactor types. The results show the improvement in modeling accuracy and highlight the role of oxygen and nutrient levels on the shifts. The approach showcases the use of data-driven insights to effectively utilize limited experimental data to develop robust mechanistic models.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"191 ","pages":"Article 108822"},"PeriodicalIF":3.9,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424002400/pdfft?md5=7997adf5ee2030eb9c80b9ddacea1b76&pid=1-s2.0-S0098135424002400-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142049601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Novel terminal region computation method for quasi-infinite horizon NMPC","authors":"Guilherme Augusto Silva de Souza, Darci Odloak","doi":"10.1016/j.compchemeng.2024.108819","DOIUrl":"10.1016/j.compchemeng.2024.108819","url":null,"abstract":"<div><p>An algorithm for invariant region characterization for a nonlinear system controlled by an LQR is proposed. The quasi-infinite horizon nonlinear model predictive controller formulation is extended for zone control with optimizing targets. The novel invariant region characterization proposed promotes hypervolume gains of up to two orders of magnitude for an unstable CSTR. Extension of the NMPC formulation to the case of zone control with optimizing targets improves the formulation’s practical deployment capability. A comparison between QIH-NMPC and NMPC with a terminal equality constraint is drawn, showing considerable closed-loop performance loss when employing a terminal equality constraint. The proposed invariant region shows feasibility set gains from the proposed invariant region characterization, when compared to a recent approach. Closed-loop simulations of both controllers from the enlarged feasibility set show how sensible the closed-loop performance is to one infeasible controller iteration.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108819"},"PeriodicalIF":3.9,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141938879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chong Liu , Chengyu Han , Chenxi Gu , Wei Sun , Jingde Wang , Xun Tang
{"title":"Operating condition design with a Bayesian optimization approach for pharmaceutical intermediate batch concentration","authors":"Chong Liu , Chengyu Han , Chenxi Gu , Wei Sun , Jingde Wang , Xun Tang","doi":"10.1016/j.compchemeng.2024.108813","DOIUrl":"10.1016/j.compchemeng.2024.108813","url":null,"abstract":"<div><p>In the synthesis of pharmaceutical intermediates, concentration is commonly employed to separate the product and recycle the solvents. To achieve a cost-effective manufacturing, operating parameters shall be adjusted over time, which could traditionally be achieved based on dynamic simulation, but with significant computation cost. In this work, we introduced a Bayesian optimization approach to design the optimal operating condition of a pharmaceutical intermediate in the production of Lamivudine. Using a Gaussian process regression as the surrogate model, the approach tremendously reduced the computational cost in searching for the optimal design. In comparison to other commonly used intelligent optimization algorithms, the results demonstrate that the presented approach confers evident advantages, especially in reducing the tendency of getting trapped in local optima and in improving the speed of convergence to an optimal solution.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108813"},"PeriodicalIF":3.9,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recurrent neural network-based prediction of O-GlcNAcylation sites in mammalian proteins","authors":"Pedro Seber, Richard D. Braatz","doi":"10.1016/j.compchemeng.2024.108818","DOIUrl":"10.1016/j.compchemeng.2024.108818","url":null,"abstract":"<div><p>O-GlcNAcylation has the potential to be an important target for therapeutics, but a motif or an algorithm to reliably predict O-GlcNAcylation sites is not available. Current predictive models are insufficient as they fail to generalize, and many are no longer available. This article constructs recurrent neural network models to predict O-GlcNAcylation sites based on protein sequences. Different datasets are evaluated separately and assessed in terms of strengths and issues. Within a given dataset, results are robust to changes in cross-validation and test data as determined by nested validation. The best model achieves an F<span><math><msub><mrow></mrow><mrow><mn>1</mn></mrow></msub></math></span> score of 36% (more than 3.5-fold greater than the previous best model) and a Matthews Correlation Coefficient of 35% (more than 4.5-fold greater than the previous best model), and, for the F<span><math><msub><mrow></mrow><mrow><mn>1</mn></mrow></msub></math></span> score, 7.6-fold higher than when not using any model. Shapley values are used to interpret the model’s predictions and provide biological insight into O-GlcNAcylation.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108818"},"PeriodicalIF":3.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141963120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Toward understandable semi-supervised learning fault diagnosis of chemical processes based on long short-term memory ladder autoencoder (LSTM-LAE) and self-attention (SA)","authors":"Yang Jing , Xiaolong Ge , Botan Liu","doi":"10.1016/j.compchemeng.2024.108817","DOIUrl":"10.1016/j.compchemeng.2024.108817","url":null,"abstract":"<div><p>Fault diagnosis and localization play vital role in chemical process monitoring. Finding the root cause of fault accurately and timely is the key to avoid serious accidents and ensure process safety. Unfortunately, most deep learning-based models only involves in predicting fault state and interpretability is still not fully explored. Besides, lack of labeled samples in practical situations makes supervised learning difficult to implement. To circumvent the obstacle, semi-supervised learning based on long short-term memory ladder autoencoder is combined with self-attention mechanism, which is intended to establish interpretable model by explicitly clarifying the corresponding relationship between abnormal variables and faults. Using Tennessee Eastman process and practical high-purity carbonate production process as benchmark, fault diagnosis and identification performance of proposed LSTM-LAE-SA is validated, and interpretability analysis is performed to demonstrate its capabilities in abnormal variable locations. The developed understandable model could improve operator's trust and industrial application in fault diagnosis system.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108817"},"PeriodicalIF":3.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141950332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Achilleas L. Arvanitidis , Margaritis Kostoglou , Michael C. Georgiadis
{"title":"Modeling, optimization and control of a ceramic tunnel kiln for consistent product quality under changing production demands","authors":"Achilleas L. Arvanitidis , Margaritis Kostoglou , Michael C. Georgiadis","doi":"10.1016/j.compchemeng.2024.108812","DOIUrl":"10.1016/j.compchemeng.2024.108812","url":null,"abstract":"<div><p>This study presents a detailed physics-based model focusing on an industrial tunnel kiln under feedback control. Initially, an empirical sintering model is integrated into the kiln model to accurately predict the product outlet density, a quality-defining parameter reflecting firing process efficacy. Afterwards, the initial steady-state burner valve positions are determined using industrial temperature data. Subsequently, the interactions between gas temperatures and burner valve positions are quantified through the investigation of the Relative Gain Array. A systematic derivation of optimal set-points for different production rates is then carried out, aiming at minimizing energy consumption while meeting end-product quality specifications. The PID controllers are tuned using a dynamic optimization approach, which involves the minimization of integral criteria. Finally, a case study is conducted to evaluate the efficacy of the optimal set-points under varying production rates. The results demonstrate exceptional system response, thus indicating that firing curves should adapt to production rates for consistently producing quality products.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108812"},"PeriodicalIF":3.9,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141840403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ittisak Promma, Marc G. Aucoin, Nasser Mohieddin Abukhdeir, Hector Budman
{"title":"A coupled metabolic flux/compartmental hydrodynamic model for large-scale aerated bioreactors","authors":"Ittisak Promma, Marc G. Aucoin, Nasser Mohieddin Abukhdeir, Hector Budman","doi":"10.1016/j.compchemeng.2024.108806","DOIUrl":"10.1016/j.compchemeng.2024.108806","url":null,"abstract":"<div><p>Spatial variation of microorganism populations in stirred-tank bioreactors, caused by the interactions of complex multiphase flows and microorganism metabolism, results in undesirable performance characteristics and significant challenges in scale-up activities. In this work, a novel modelling approach is developed to investigate these coupled processes in bioreactors, which involves the integration of a computational fluid dynamics-informed compartmental hydrodynamic and a dynamic flux balance (DFB) model. This coupling poses significant computational challenges especially when dealing with transient scenarios. To tackle these challenges we developed a fast point-location algorithm to solve the DFB model at different bioreactor locations. To validate the presented modelling approach, a binary search tree-based metabolic model for <em>E. coli</em> was developed and integrated with a flow-informed compartmental model of a large-scale four-impeller aerated bioreactor in fed-batch operation. The model results exhibit favorable agreement with the concentration profiles reported in literature for both lab-scale and industrial scale bioreactors. Furthermore, the ability of the approach to deal with transient scenarios permitted to study the effect of oxygen closed loop control responses and the occurrence of oscillatory behaviour which were crucial to explain part of the data.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108806"},"PeriodicalIF":3.9,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424002242/pdfft?md5=6aecf3d2b276b79c672f5f820290615e&pid=1-s2.0-S0098135424002242-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141839856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal measurement-based cost gradient estimate for feedback real-time optimization","authors":"Lucas Ferreira Bernardino, Sigurd Skogestad","doi":"10.1016/j.compchemeng.2024.108815","DOIUrl":"10.1016/j.compchemeng.2024.108815","url":null,"abstract":"<div><p>This work presents a simple and efficient way of estimating the steady-state cost gradient <span><math><msub><mrow><mi>J</mi></mrow><mrow><mi>u</mi></mrow></msub></math></span> based on available uncertain measurements <span><math><mi>y</mi></math></span>. The main motivation is to control <span><math><msub><mrow><mi>J</mi></mrow><mrow><mi>u</mi></mrow></msub></math></span> to zero in order to minimize the economic cost <span><math><mi>J</mi></math></span>. For this purpose, it is shown that the optimal cost gradient estimate for unconstrained operation is simply <span><math><mrow><msub><mrow><mover><mrow><mi>J</mi></mrow><mrow><mo>ˆ</mo></mrow></mover></mrow><mrow><mi>u</mi></mrow></msub><mo>=</mo><mi>H</mi><mrow><mo>(</mo><msub><mrow><mi>y</mi></mrow><mrow><mi>m</mi></mrow></msub><mo>−</mo><msup><mrow><mi>y</mi></mrow><mrow><mo>∗</mo></mrow></msup><mo>)</mo></mrow></mrow></math></span> where <span><math><mi>H</mi></math></span> is a constant matrix, <span><math><msub><mrow><mi>y</mi></mrow><mrow><mi>m</mi></mrow></msub></math></span> is the vector of measurements and <span><math><msup><mrow><mi>y</mi></mrow><mrow><mo>∗</mo></mrow></msup></math></span> is their nominally unconstrained optimal value. The derivation of the optimal <span><math><mi>H</mi></math></span>-matrix is based on existing methods for self-optimizing control and therefore the result is exact for a convex quadratic economic cost <span><math><mi>J</mi></math></span> with linear constraints and measurements. The optimality holds locally in other cases. For the constrained case, the unconstrained gradient estimate <span><math><msub><mrow><mover><mrow><mi>J</mi></mrow><mrow><mo>ˆ</mo></mrow></mover></mrow><mrow><mi>u</mi></mrow></msub></math></span> should be multiplied by the nullspace of the active constraints and the resulting “reduced gradient” controlled to zero.</p></div>","PeriodicalId":286,"journal":{"name":"Computers & Chemical Engineering","volume":"189 ","pages":"Article 108815"},"PeriodicalIF":3.9,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0098135424002333/pdfft?md5=a98cf7660f075255475fa08c633293d7&pid=1-s2.0-S0098135424002333-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141849410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}