QCD* maintenance and management is presenting a challenge in site operations such as equipment inspection and maintenance. Currently, site workers suffer more burden than before due to expert operators' aging, labor shortages, reduced budget for maintenance, increasingly advanced and complex equipment, and rising frequency of failures caused by the aged equipment and facilities. Site operation managers are striving to improve work environments, reduce personnel needs and improve equipment operation rates by carrying out preventive maintenance and effectively leveraging digitized equipment data and other information. "Meister Digital Field Work", Toshiba Digital Solutions' site operation support solution, is transforming the workstyles of field operators and improving QCD of site operation. Let's look at how this innovative solution helps solving the site operation challenges faced by production sites and infrastructure facilities.
* QCD: Quality, Cost, Delivery
One of the vital functions of devices and equipment management in production plants, power plants and the like is to contribute to the effective use of company's assets and to improve productivity.
A critical challenge of asset management is keeping equipment in operation without stoppage for long periods of time, and operating it in line with operation plans. The equipment status shall be monitored in real-time, and inspections and maintenance shall be conducted to sustain equipment operation and rapid recovery in the event of a failure are required. Critical social infrastructure equipment, such as that used in the energy sector, must be kept running, and problems must be surely prevented. This is accomplished by managing equipment through thorough implementation of regular maintenance, and the like.
However, with the rising demand to cut maintenance costs and tackle the issue of aging equipment, this asset management is pressed to be more efficient and sophisticated. Attention is being turned to preventive maintenance, which prevents equipment failures and stoppages by sequential collecting and analyzing the equipment status information and regular operation data.
This preventative maintenance is being achieved through worksite information digitization, using digital data. By visualizing equipment operation conditions based on data such as temperature and vibration those are collected by sensors, signs of possible abnormalities are identified and are quickly dealt with. Data is analyzed with high precision, and predictions are issued regarding which devices and components are likely to experience problems in which timing. This assists in future maintenance plans and day-to-day regular inspections.
However, these preventive maintenance will not be realized by merely digitizing information of manufacturing or infrastructure equipment alone. The challenges of asset management in site operations must be tackled before that. Peoples who are in charge of asset management struggle with insufficient work force due to human resource shortages and shrinking personnel expense budgets, and with the increased operations burdens caused as operators are expected to be multi-skilled in order to make up these human resource problems. The number of equipment failures and operation errors are also rising due to aged equipment in long-term operation and the greater complexity resulting from additional installation. Furthermore, while skilled workers are aging, site operations depends on knowledge and know-how of such workers. Succeeding those knowledge and know-how to successors is difficult, and this is impeding productivity improvements.
If left unaddressed, this makes it difficult to maintain and manage site operation QCD. There is a need for measures for appropriately supporting site workers and enabling them to carry out their work effectively.
In order to address these issues, we have begun providing the mobile device-based worksite operations support solution, "Meister Digital Field Work". It integrates asset management data such as previous inspection information, operation information and failure information, with Internet of Things (IoT) data from sensors, etc., and makes it possible to access to the data needed for site operations from mobile devices. This supports accurate decision-making and effective operations by all worksite operators (Fig. 1).
For the development of this solution, we observed many worksites and we participated in round inspections of power companies and manufacturers, and started our development process with identifying issues and problems of worksite operations.
Worksite operations requires a wide range of inspection for individual devices, such as visual inspections of analog meters including pressure gauges, oil pressure indicators and so on. Workers carries around heavy, bulky printed materials, and searches for the information necessary for individual inspection operations at the worksite, crouching down and squeezing into tight spots, or working in high, potentially dangerous areas. They walk or use bicycles to make their rounds of equipment scattered across extensive worksite grounds and hand-write each and every inspection result in a report within the limited time available to them. Going on these rounds of worksites together with site operators, we felt that in order to improve worksite operation QCD, shorten equipment recovery times and implement preventive maintenance would be absolutely essential to dramatically streamline the processes.
We used UX design* to organize the situations we discovered through our actual site observation, and came to identify the following worksite operators' needs out of these worksite operation issues.
Based on these needs, we developed a concept of aggregating all kinds of information in mobile devices and making it possible to rapidly and easily to access necessary information. We strove to develop a solution that all site operators would find "intuitive," enabling anyone to reliably work with inspection and maintenance information; "reliable," enabling them to handle even new work or situations with which they had no previous experience by using accumulated know-how; and "highly informative," enabling them to access as much information as possible, anywhere, at any time.
* UX design: Design method that uses human-centered design methodologies to produce a better User eXperience
"Meister Digital Field Work" was developed with the aim of resolving issues identified through actual site observation and experience. It aims to address the following problems.
It meets the need to intuitively and surely handle work procedures and the information necessary to carry out operations, by making it possible to confirm the device and area information and work items at worksites and register the results of the work there as well. The inspection results can be easily input by touch commands. As it supports item selection methods as well, the site operators can proceed the work more accurately and speedily than recording results on paper.
To meet the need to work without concern for the new work or situations for their first time by accessing references, it makes it possible to easily register with not only texts data but with pictures or videos to surely transfer them as know-how in an easy to understand manner.
To meet the need to carry around a large amount of information and access it at any time, it correlates the IoT data that is steadily stored each day with asset management data, and makes it possible to easily search data and quickly access the results of analysis. Compared to looking up information in binders of printed documents, this solution also enables to reach necessary information extremely quickly. In addition to being able to easily call up procedures, instructions, site photos, and the like, it also can display trend graphs that visually represent inspection histories. This makes it easier to gain new insights regarding change points based on data distributions, data relationships, time-series tendency, and so on. Furthermore, in the future, "Meister Digital Field Work" will be linked to "Meister AR Suite*," our site operation digitization solution. This will make it possible for even inexperienced operators to perform site work smoothly, from a vantage similar to that of an expert, by capturing the objects to inspect through a mobile device's camera and following the guidance information overlaid over the image shown on the screen.
* Meister AR Suite is introduced in detail in #04.
In these ways, "Meister Digital Field Work" takes advantage of mobile devices with their superb mobility and ease of operation, to access and record various information related to inspections and maintenance, which have been performed manually and on paper in many worksites. Furthermore, by combining this with backend asset management data and IoT data, it makes it easier to perform data analysis and make use of real-time data at worksites, and supports operation efficiency and quality improvements.
"Meister Digital Field Work" makes asset management data much richer than it has ever been. By integrating and analyzing them with IoT data, it will become possible to identify specific causal relationships which were not noticed before, and link them to optimized equipment maintenance activities. This makes it happen to realize even more precise equipment planning and preventive maintenance by effectively implementing the equipment PDCA cycle of "Plan" (formulating equipment plans), "Do" (implementing inspection and maintenance), "Check," (evaluating effectiveness based on plans and results) and "Action" (reviewing and revising equipment plans) (Fig. 2).
"Meister Digital Field Work" has tremendous potential to transform work style of site operators and contribute to the overall optimization of asset management. By tackling the challenges of increased workloads due to increasingly advanced, complicated and aging equipment besides cost reductions, labor shortages, and required knowledge transfers and successions from current generation to the next generation, it can leverage asset management to gain customer's competitive advantage.
* The corporate names, organization names, job titles and other names and titles appearing in this article are those as of November 2018.