Assessment of the effectiveness of corrective maintenance of an oil pump using the proportional intensity model (PIM)

PurposeComplex repairable systems (CRSs) are generally modeled by stochastic processes called “point processes.” These are generally summed up in the nonhomogeneous Poisson process (NHPP) and the renewal process (RP), which represent the minimum and maximum repair, respectively. However, the industrial environment affects systems in some way. This is why the main objective of this work is to model the CRS with a concept reflecting the real state of the system by incorporating an indicator in the form of covariate. This type of model, known as the proportional intensity model (PIM), will be analyzed with simulated failure data to understand the behavior of the failure process, and then it will be tested for real data from a petroleum company to evaluate the effectiveness of corrective actions carried out.Design/methodology/approachTo solve the partial repair modeling problem, the PIM was used by introducing, on the basis of the NHPP model, a multiplicative scaling factor, which reflects the degree of efficiency after each maintenance action. Several values of this multiplicative factor will be considered to generate data. Then, based on the reliability and maintenance history of 12-year pump's operation obtained from the SONATRACH Company (south industrial center (CIS), Hassi Messaoud, Algeria), the performance of the PIM will be judged and compared with the model of NHPP and RP in order to demonstrate its flexibility in modeling CRS. Using the maximum likelihood approach and relying on the Matlab software, the best fitting model should have the largest likelihood value.FindingsThe use of the PIM allows a better understanding of the physical situation of the system by allowing easy modeling to apply in practice. This is expressed by the value which, in this case, represents an improvement in the behavior of the system provided by a good quality of the corrective maintenance performed. This result is based on the hypothesis that modeling with the PIM can provide more clarification on the behavior of the system. It can indicate the effectiveness of the maintenance crew and guide managers to confirm or revise their maintenance policy.Originality/valueThe work intends to reflect the real situation in which the system operates. The originality of the work is to allow the consideration of covariates influencing the behavior of the system during its lifetime. The authors focused on modeling the degree of repair after each corrective maintenance performed on an oil pump. Since PIM does not require a specific reliability distribution to apply it, it allows a wide range of applications in the various industrial environments. Given the importance of this study, the PIM can be generalized for more covariates and working conditions.

Towards the assessment of business process knowledge intensity – a systematic literature review

PurposeThe aim of the article is to propose an integrated definition of knowledge-intensive business processes (kiBPs) and a model of business process (BP) knowledge intensity and develop holistic criteria and measures for the assessment of BP knowledge intensity.Design/methodology/approachA qualitative systematic literature review (SLR) was carried out as a means of evaluating and interpreting all available research relevant to the research topic, in this case, BP knowledge intensity. The SLR is based on the resources of the ProQuest, Springer Nature and ScienceDirect full-text databases. Regarding inclusion criteria, the authors considered peer-reviewed journals and conference proceedings published in English in the last 10 years. The results were summarized and synthesized narratively.FindingsBased on the review, the authors classified existing knowledge intensity definitions, starting with knowledge-intensive economy or country, sectors and services, through knowledge-intensive organizations, BPs, to tasks. Then, an integrated definition of kiBPs was proposed and the business process knowledge intensity model encompassing three domains developed. Finally, 12 knowledge intensity criteria with measures were proposed.Originality/valueThe major value of this research is that it presents a novel approach to understanding BP knowledge intensity and kiBPs. By creating the BP knowledge intensity model, supplemented by the assessment criteria and measures, the authors contribute to the more effective management of kiBP, help find similarities and differences between various knowledge-intensive processes, as well as provide important implications for their effective management and research.

Application of Histogram Equalization for Image Enhancement in Corrosion Areas

In this paper, an image enhancement algorithm is presented for identification of corrosion areas and dealing with low contrast present in shadow areas of an image. This algorithm uses histogram equalization processing under the hue-saturation-intensity model. First of all, an etched image is transformed from red-green-blue color space to hue-saturation-intensity color space, and only the luminance component is enhanced. Then, part of the enhanced image is combined with the original tone component, followed by saturation and conversion to red-green-blue color space to obtain the enhanced corrosion image. Experimental results show that the proposed method significantly improves overall brightness, increases contrast details in shadow areas, and strengthens identification of corrosion areas in the image.