Technical and operational feasibility of technological advancements in CM

It is crucial to assess the technical and operational feasibility of the technological measures that we have explained in detail in the subsection 2.2.1 in order to illustrate if they can be actually implemented in the current industrial contexts and if so conclude further how they will actually solve the challenges facing the CM systems. Indeed, if the advanced condition monitoring tools and systems, chosen by the relevant company, appear to be convenient in terms of their adaptation to the industrial environment, then they can be highly efficient and of a crucial help to the machinery users in relation to the early detection of degradation or the upcoming issues. But if the applied programs are not adequate or even not feasible or installed in an unsystematic and chaotic manner, the outputs could be disappointing when it comes to the overall operational costs and levels of accuracy and safety. In this case, the efforts of installation would be a waste of time and financial resources. When studying the feasibility of the novel CM systems, it is essential to assimilate that even though the related programs might be technically and operationally feasible, they could be not be feasible from an organizational or structural perspective and therefore ought not to be applied. For this reason, the kind of industrial environment, the status of machinery, the type of assets and the company’s culture and policies are real factors to be taken into account on this matter. It is obvious that these variables differ from an organization to another. This is why; we will mostly concentrate on an overall assessment of the feasibility of advanced CM techniques.

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In order to implement the new invented CM mechanisms as an effective approach for identifying the maintenance requirements of the machinery in question and upgrade the quality of industrial procedures, some conditions must be met. Factors such as the easy physical access to the installation of the condition monitoring system, the manageable levels of complexity of the data acquisition and data processing must be obviously considered.

Moreover, the cost related to the installation, operation and data processing or any other costs of the means utilized to perform the condition monitoring tasks should be examined closely before any implementation. In addition to that, the adopted CM approaches or techniques should be known and acknowledged by every single level of the firm, starting by the top leaders and executive managers till the engineers and operators that shall perform the related operations. The company has to make sure that everyone involved must acquire the necessary training, competences and expertise to handle the potential changes to the existing CM systems in an effective and safe manner. The needed amounts of resources to perform the established monitoring and maintenance activities should be subsequently determined and assigned.

We are witnessing today some significant improvements related to the utilized software in CM systems. Therefore, to insure an operational and technical effectiveness of the chosen software and the success of its operations, the company must make sure that it allows above all answering some basic demands. In other quarters, it should permit a better integration of all information associated to the machine health status in one unified program. The latter must have an open and an easy access to all involved parties and be ready to be modified when needed. The chosen software must acquire a solid and coherent sharing of data across the functional lines. For that, the adjustment to the machinery parameters, the environmental and the timing variables has to be on point; otherwise the program won’t be capable of delivering the results. Multiple companies can use extremely advanced software and still face a total failure when it comes to its establishment and that because it hasn’t prepared competently for its installation and usage or hasn’t checked its technical feasibility. The selected software should be able to reduce lengthy learning curves and eliminate any possible software platform compatibility problems. In case it doesn’t succeed to accomplish so, the company must replace it by another program or ask the original manufacturer to modify its parameters if this is doable. We have previously clarified that the developed software is mostly utilized in correlation with the advanced remote control instruments. These devices are becoming more important with time as environmental laws become more biding and decreasing funding considerably diminishes the available workforce. The economic feasibility of these tools depends on their manufacturing characteristics and the company itself. Concerning the technical and operational ones, they are more linked to the specific technical characteristic of the site or the facility, the staffing levels and expertise, the size and complexity of the machinery, the geographic location, the regulatory requirements and standards and the nature and frequency of operations where monitoring and control would be helpful. Furthermore, the company must make sure that the selected remote devices should be compatible with the adopted techniques (thermal imaging, vibration, ultrasonic...). More importantly, the feasibility of the software and the used remote tools is directly connected to the ability of the company on establishing clear and unified semantic regulations and principles so as the analysis of data would be simpler and more accurate. If all these conditions are applied, the

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industrial organization would find it quite easy to install the advanced CM programs and follow the development of their related processes.

On the other side, a great number of industrial corporations utilize wireless sensors. The scope of developing low-power microelectronics; the miniaturization, the manufacturing of sensor material, the design and the creation of complex and precise shapes have guided the industrials to the comprehension of intelligent mechanisms and programs for health and environmental monitoring reasons. With the development of materials science and technological advancements joined with the great opportunities starting from wireless networking and the usage of the Internet, the scope of sensor appliance has expanded significantly. Nevertheless, resourceful initiatives such as wireless monitoring mechanisms will build up a competitive advantage if the systems in question can function economically with resistant technical capabilities. The wireless condition monitoring technology usually employs interface modules in order to gather vibration or temperature information mostly from machinery in the industrial facility and then transmit the collected data to the software system responsible of diagnostic. Wireless sensors are consequently considered as feasible alternatives to handheld or hardwired condition monitoring systems, especially compelling for primary equipment which do not demand real-time machinery protection but necessitate a more regular monitoring percentage than the portable regime to determine possible deficiency modes. Wireless sensors are proven to be quite useful for applications that are logistically complicated or dangerous to monitor or control by handheld information collectors, or could probably call for more recurrent sampling than the walk-around route can financially sponsor.

When talking about the technological enhancements in the CM systems, we ultimately think about the introduction of the industry 4.0 in the industrial structures. The IoT is a first factor to be considered when analyzing the matter. Usually, a condition monitoring solution that is performed by an IoT industrial maneuver is carried out by equipping first of all the industrial machinery with sensors that will gather information on a large range of variables indicating its health and performance such as temperature, pressure, vibration frequency. Once collected, the data is transferred to the cloud. Following that, the cloud software accumulates the data from the used sensors and applies analytics devices to transform time-series data into descriptive insights concerning the machinery health state and the relevant operational variables. A condition monitoring solution apprehends the findings and passes them over to the users in an all-inclusive manner like in the form of diagrams or charts, etc. If the situation diverges from the norm, the condition monitoring resolution might as well send an alert to the maintenance managers, informing them about the degradation of the machines’ condition.

Typically, the information provided by the condition monitoring system offers an important insight about the actual state of the machinery and could be executed to indirectly control the quality of goods in production, through monitoring the condition of the equipment’s parts. For instance, in paper manufacturing, condition monitoring solutions aid to monitor the quality of paper being fabricated through monitoring the state of roll presses. Still, the usefulness of condition monitoring isn’t limited to quality control. Its findings could be employed to predict future machinery performance, forecast which equipment components are more likely to fail and determine on the scope of maintenance tasks based on the anticipated levels of

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deterioration. (Shiklo, 2018). The IoT techniques operational feasibility depends to a large extent on the capability of the company to choose the right sensors and software to undertake the specific monitoring activities. To ensure a complete integration of the IoT tools, it must establish an accurate execution of the IIoT steps and a thorough follow up of the applied procedures in order to achieve a better outcome. Companies have obviously become more interested in the computer based systems for health monitoring utilizing procedures and methodologies developed in the Artificial Intelligence field. They rely more often therefore on what they call “expert systems. An “expert system” is an intelligent computer code that employs knowledge inference methodologies or approaches to resolve issues that are seen as complicated enough to necessitate considerable human expertise for their resolution. The knowledge base of an expert system resides in facts and heuristics. The facts constitute a body of data which is largely and commonly agreed upon by specialists in the related domain.

While heuristics are defined as rules of judgment and rules of good guessing or prediction that symbolize expert-level decision making in the industrial field. (Meher-Homji, 1985). At this point in time, it has been proven that a great variety of expert system software providing prognostics and diagnostics of the relevant machinery are today absolutely feasible technically and operationally. Still some industrials still believe that “expert systems” are regarded as an aid to the maintenance engineers or the monitoring specialists and aren’t made to out think the experts or replace them in anyway while others maintain an opposite view.

Consequently, it has been established that condition and cloud based prognostics and diagnostics provide the needed opportunities to decrease loss engendered by equipment deficiency and deferment in planning for maintenance tasks and spare parts. Still, the time complexity of the predictive algorithms employed for forecasting forthcoming component faults or the remaining useful life of critical machinery elements holds a crucial part in indicating the accuracy and also the feasibility of prognostics mechanisms. Moreover, the architecture and internal characteristics of the cloud computing programs adopted by the firm in question plays a significant role in determining how these advanced systems would be feasible.

As we have seen there are multiple factors deciding to what extent the explained technological programs and tools are feasible in a technical and an operational contexts.

Again, this would depend on the economic capabilities of the company to install these improvements and establish the adequate follow up tasks to maintain their lasting performance.

2.3.4 Technical and operational feasibility of technological