A framework for implementing robotic process automation projects

Robotic process automation is a disruptive technology to automate already digital yet manual tasks and subprocesses as well as whole business processes rapidly. In contrast to other process automation technologies, robotic process automation is lightweight and only accesses the presentation layer of IT systems to mimic human behavior. Due to the novelty of robotic process automation and the varying approaches when implementing the technology, there are reports that up to 50% of robotic process automation projects fail. To tackle this issue, we use a design science research approach to develop a framework for the implementation of robotic process automation projects. We analyzed 35 reports on real-life projects to derive a preliminary sequential model. Then, we performed multiple expert interviews and workshops to validate and refine our model. The result is a framework with variable stages that offers guidelines with enough flexibility to be applicable in complex and heterogeneous corporate environments as well as for small and medium-sized companies. It is structured by the three phases of initialization, implementation, and scaling. They comprise eleven stages relevant during a project and as a continuous cycle spanning individual projects. Together they structure how to manage knowledge and support processes for the execution of robotic process automation implementation projects.

     

Laser pyrolysis in papers and patents

Journal of Intelligent Manufacturing - This paper presents a critical review of laser pyrolysis. Although this technology is almost 60 years old, in literature many researchers, both from...     

Structure and Magnetic Property Control of Copper Hydroxide Acetate by Non‐Classical Crystallization

Copper hydroxide acetate (CHA), one layered hydroxide compound with tunable magnetism, attracts great interest because of its potential applications in memory devices. However, ferromagnetism for CHA is only demonstrated by means of GPa pressure. Herein, a new method is reported, involving the combination of different crystallization pathways to control crystallization of amorphous CHA toward the formation of CHA/polymer composites with tunable magnetic properties and even a tunability that can be tested at room temperature. By using poly[(ethylene glycol)₆ methyl ether methacrylate]‐block‐poly[2‐(acetoacetoxy) ethyl methacrylate] (PEGMA‐b‐PAEMA) diblock copolymers as additives in combination with a post‐treatment process by ultracentrifugation, it is demonstrated that CHA and PEGMA‐b‐PAEMA form composites exhibiting different magnetic properties, depending on CHA in‐plane nanostructures. Analytical characterization reveals that crystallization of CHA is induced by ultracentrifugation, during which CHA nanostructures can be well controlled by changing the degrees of polymerization of the PEGMA and PAEMA blocks and their block length ratios. These findings not only present the first example of using crystallization from polymer stabilized amorphous precursors toward the generation of magnetic nanomaterials with tunable magnetism but also pave the way for the future design of functional composite materials.     

On the simulation,economic analysis,and life cycle assessment of batch-mode organic solvent recovery alternatives for the pharmaceutical industry

This study explores design alternatives for the purification and possible reuse of low-volume organic solvents waste streams in pharmaceutical manufacturing. Solvent use has a large impact on the life cycle of pharmaceutical processes, as typically 80–90% of the total mass used in the production of an active pharmaceutical ingredient is attributed to solvent use. Solvents are not consumed in pharmaceutical processes so they exit the process as waste. These waste streams are usually disposed of using incineration; therefore, generating significant life cycle emissions from disposal and replacement of virgin solvent. Solvent recovery efforts are generally limited to large-volume waste streams. However, results show that solvents in low-volume streams can also be economically recovered using a versatile multi-campaign solvent recovery skid. Three different solvent waste streams were evaluated, and 85.3% reduction in total emissions and 86.3% reduction in operating costs were achieved. Investment in the solvent recovery system was determined to have a payback period of 4.5 years and a 28% IRR over 10 years. A life cycle impact assessment shows impacts on the human health, ecosystems, and resources categories have been reduced by 82.4, 85.1, and 87.1%, respectively.     

Real‐time updating of structural mechanics models using Kalman filtering,modified constitutive relation error,and proper generalized decomposition

The paper aims at proposing a new strategy for real‐time identification or updating of structural mechanics models defined as dynamical systems. The main idea is to introduce the modified constitutive relation error concept, which is a practical tool that enables to efficiently solve identification problems with highly corrupted data, into the Kalman filtering, which is a classical framework for data assimilation. Furthermore, a PGD‐based model reduction method is performed in order to optimize capabilities of the online updating strategy. Performances of the proposed approach, in terms of robustness gain and computational cost reduction, are illustrated on several unsteady thermal applications. Copyright © 2015 John Wiley & Sons, Ltd.