The operational performance of a chemical process plant highly depends on the assets' condition and maintenance practices. As chemical processes are highly complex systems, increasing the risk frequencies and their interactions, the maintenance planning becomes crucial for stable operation. This paper provides a critical analysis of the recently developed approaches for asset maintenance approaches in the chemical industry. The strategies include corrective maintenance, time-based, risk-based, condition-based and opportunistic maintenance. Various methods on selecting the optimal maintenance strategy are discussed as well. This paper also evaluates reliability issues in chemical plants and integrated sites encompassing the maintenance optimisation. Several directions for potential future improvements are proposed based on this analysis, as follows: (i) potential study of exploiting production or other opportunities to postpone or conduct earlier maintenance; (ii) joint optimisation of spare part ordering strategy and data-driven maintenance planning study is needed; (iii) fault propagation modelling of structural dependent units to facilitate proper maintenance planning; (iv) a framework or tool that consider quantitative and qualitative time-variant data inputs is lacking for business-informed asset maintenance.

State estimation is a fundamental part of monitoring, control, and real-time optimization in continuous pharmaceutical manufacturing. For nonlinear dynamic systems with hard constraints, moving horizon estimation (MHE) can estimate the current state by solving a well-defined optimization problem where process complexities are explicitly considered as constraints. Traditional MHE techniques assume random measurement noise governed by some normal distributions. However, state estimates can be unreliable if noise is not normally distributed or measurements are contaminated with gross or systematic errors. To improve the accuracy and robustness of state estimation, we incorporate robust estimators within the standard MHE skeleton, leading to an extended MHE framework. The proposed MHE approach is implemented on two pharmaceutical continuous feeding-blending system (FBS) configurations which include loss-in-weight (LIW) feeders and continuous blenders. Numerical results show that our MHE approach is robust to gross errors and can provide reliable state estimates when measurements are contaminated with outliers and drifts. Moreover, the efficient solution of the MHE realized in this work, suggests feasible application of on-line state estimation on more complex continuous pharmaceutical processes.

The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present proof of concept results for phase resetting of the clock via model predictive control.

A novel and versatile plasma reactor was used to modify Polyethersulphone commercial membranes. The equipment was applied to: i) functionalize the membranes with low-temperature plasmas, ii) deposit a film of poly(methyl methacrylate) (PMMA) by Plasma Enhanced Chemical Vapor Deposition (PECVD) and, iii) deposit silver nanoparticles (SNP) by Gas Flow Sputtering. Each modification process was performed in the same reactor consecutively, without exposure of the membranes to atmospheric air. Scanning electron microscopy and transmission electron microscopy were used to characterize the particles and modified membranes. SNP are evenly distributed on the membrane surface. Particle fixation and transport inside membranes were assessed before- and after-washing assays by X-ray photoelectron spectroscopy depth profiling analysis. PMMA addition improved SNP fixation. Plasma-treated membranes showed higher hydrophilicity. Anti-biofouling activity was successfully achieved against Gram-positive () and -negative ( Typhimurium) bacteria. Therefore, disinfection by ultrafiltration showed substantial resistance to biofouling. The post-synthesis functionalization process developed provides a more efficient fabrication route for anti-biofouling and anti-bacterial membranes used in the water treatment field. To the best of our knowledge, this is the first report of a gas phase condensation process combined with a PECVD procedure in order to deposit SNP on commercial membranes to inhibit biofouling formation.

Horizontal bubbly flow is widely encountered in various industrial systems because of its ability to provide large interfacial areas for heat and mass transfer. Nonetheless, this particular flow orientation has received less attention when compared to vertical bubbly flow. Owing to the strong influence due to buoyancy, the migration of dispersed bubbles towards the top wall of the horizontal pipe generally causes a highly asymmetrical internal phase distributions, which are not experienced in vertical bubbly flow. In this study, the internal phase distribution of air-water bubbly flow in a long horizontal pipe with an inner diameter of 50.3 mm has been predicted using the population balance model based on direct quadrature method of moments (DQMOM) and multiple-size group (MUSIG) model. The predicted local radial distributions of gas void fraction, liquid velocity and interfacial area concentration have been validated against the experimental data of Kocamustafaogullari and Huang (1994). In general, satisfactory agreements between predicted and measured results were achieved. The numerical results indicated that the gas void fraction and interfacial area concentration have a unique internal structure with a prevailing maximum peak near the top wall of the pipe due to buoyancy effect.

The issues of data quality and propagation of data uncertainties into process design and plant specifications are of great current interest. Hence, two Working Parties of the European Federation of Chemical Engineers (EFCE) organized a Round Table Discussion on the topic, as part of the World Congress of Chemical Engineering (WCCE10) in Barcelona, in October 2017. The discussion was guided by industrial and academic experts, with the audience as a key part of the discussion, trying to find some answers in three areas: Data acquisition and evaluation of experimental uncertainties, tools for data reconciliation to improve their quality, and impact of data uncertainties on the process at the end. Several concrete stories are presented that demonstrate the importance of considering data quality and all possible contributions to the uncertainty of chemical process design. Difficulties associated with data quality are discussed at various levels: (1) the experimentalists (measurement issues, evaluation of uncertainties, use of consistency analysis tools); (2) model developers (capture of adequate physics, parameter regression strategies, uncertainty propagation), (3) vendors of process simulation software, and (4) process engineers (who are responsible at the end). Paths for improvements were proposed through better and more efficient communication among different participants, as well as through education.