Knowledge Capture, Cross Boundary Communication and Early Validation with Dynamic A3 Architectures

Understanding and extracting systems information is a time consuming, demanding and expensive process. Complicating factors are cross-boundary communication methods and tools. We combine an informal and formal systems engineering method; Lean manufacturing principles and Model Based systems Engineering (MBSE) resulting in Dynamic A3 architecture. Dynamic A3 Architecture is a hierarchy of overviews from super-system to sub-system that the reader can navigate through active links. We applied the method to a lube oil system of a gas turbine package. We found that Dynamic A3 Architecture can ease internal and cross boundary communication, train new employees, facilitate knowledge capture, and share common understanding of the “system of interest”. A functional sequence diagram, which is a hybrid of a state and functional diagram, can assist in early validation of process applications. Introduction Dresser-Rand AS is located in Kongsberg (Norway), and has a long heritage of developing gas turbines from the early 1960’s. Dresser-Rand proprietary KG2 gas turbine is available from 1530 kW to 2250 kW. It is a compact, proven heavy-duty industrial gas turbine. The company has delivered over 900 KG2 units, mainly generator sets, into 54 countries worldwide. The KG2 has earned a solid reputation as a reliable and easy to maintain unit. The recently developed KG2-3G engine achieves higher power output and lower emissions. A KG2-3G engine and generator are mounted on a steel baseplate that incorporates the oil reservoir and mounting arrangements for the generator, starting and fuel systems (Figure 1).The engine and generator are enclosed in a steel structure together with all the auxiliary systems and control systems. A gas turbine package is a complicated system with subsystems and components (Figure 1). Figure 1: Main systems and components in a KG2-3G gas turbine package with the enclosure removed Lube oil system: The research was performed on a lube oil system of a KG2-3G gas turbine package (Figure 2). Most typical representations used by engineers to show the lube oil system are 3D drawings, and Piping and Instrumentation Diagrams (P&ID) (see Figure 2). The lube oil system is designed to provide the KG2-3G gas turbine engine with clean and cooled lubrication oil, at correct modulated pressure. This includes pre-lubrication, prior to start-up and cooling-down sequence following a normal stop or shutdown. The main components are positioned in proximity of the reduction gearbox, with the exception of the lube oil cooler that is usually externally mounted. The main challenge of this subsystem is to ensure sufficient oil pressure to the gearbox and turbine at two critical states; start-up and shutdown. Current way of working: In process applications, the most common communication tool is a P&ID (Figure 2 Right). It gives an overview of the physical process layout and operator feedback loops. The major issue with this kind of a diagram is that it lacks the functional view and the sequence in which the desired system is supposed to operate. Figure 2: Lube oil system of a KG2-3G gas turbine package Left: 3D model; Right: Piping and instrumentation diagram (P&ID) Why trying a new approach? We analyzed symptoms of degraded performance, determined a problem statement, and transformed this into a goal as shown (Figure 3).We observed that main communication means in Dresser-Rand are 3D models, 2D drawings, and piping/instrumentations diagrams. These models and diagrams are not only common to Dresser-Rand in particular, but also to most of the engineering companies. They represent a good visualization of the physical view but not the functional part; how does the system work, and quantified relations. Symptoms that we observed are that less experienced engineers need a lot of time to find information and they need experienced engineers to explain functionality and quantified performance. The functionality, that is the result of the dynamic cooperation of parts, is often ill understood, since it crosses physical boundaries. Engineers often poorly understand quantified system performance caused by the same cross boundary problem. Figure 3: Overview of symptoms, problem and goal Typical projects for gas turbine package engineering run for periods of 10-12 months. During the initial phase of a project, a team is established composing of a project manager and engineers (cybernetic, system mechanical, mechanical and electrical) where several of them are less experienced. The team works together in order to meet the customer needs, and try to deliver the project on schedule Dynamic A3 architectures The applied methodology is a combination of A3 and Model Based Systems Engineering (MBSE). A3 is an informal cross-boundary communication tool that emerges from LEAN (Kennedy 2010) manufacturing principles, which is a concept based upon Toyota’s Production Systems (TPS) (Sobek 2008). On an A3, the information recorded is readable and digestible. A3 is a European standard size paper 297*420mm. , Project teams around the globe. use A3’s as a source of cross boundary communication tool to solve or address various problems in their domain. Borches (Borches 2010) proposes A3’s that are two sided; one is textual and the other composing of models and visualizations. Recommended information (Borches 2010) on the visual side is physical and functional models, quantifications, and specific design choices. On an A3, authors often use color notations to relate functions and quantified relations relative to each other. MBSE is a formalized application of modeling techniques to produce and control a coherent model of the system. It is used to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase, and continuing throughout development and later life cycle phases (Friedenthal 2008). Currently, MBSE is a field of promise with a proliferation of methods, techniques, and tools. The combination of A3 and MBSE result in Dynamic A3 architecture (Figure 4). Dynamic A3 architecture is a top-level overview of any super system, in which the stakeholders can navigate both ways “top down” or “bottom up” and access relevant sub systems information at all times. It is composed of numerous A3’s hyperlinked from a database or server, and made accessible through an internal or a remote website. Rationale behind this combination is that it is a relatively light-weight approach that fits in this project-driven organization. Figure 4: Dynamic A3 architecture applied to a lube oil system of a gas turbine package Research Methodology The primary author performed action research by applying the proposed technique as well as study its impact as researcher. The evaluations methods used were surveys, observations, and instant feedback from the internal stakeholders. The author did not set up any formal meetings to gather the feedback, but the approach was rather informal on regular basis (Table 1). He found that it was less time consuming, and much easier to gather feedback instead of organizing formal meetings or workshops. Main challenge during these informal sessions was to reveal what they want to see, like, or dislike. After the creation, 10 engineers with various engineering and/or technical background did final evaluation of the dynamic A3 architecture. This was a formal meeting, where we handed out surveys and the feedback was instantly processed. Table 1: Evaluation methods; a combination of informal and formal methods Evaluation Methods During Creation (informal) Location After creation (formal) Location Instant feedback Informal interviews Observations Suggestions Likes Dislikes Personal offices/ Coffee breaks Final thesis presentation Workshop /Survey Meeting hall Current Effort Spent on Information Finding We conducted a quantitative analysis to map the current situation at Dresser-Rand AS Kongsberg. We deployed a survey with 18 project participants who individually have various years of work experience in the R&D and the gas turbine packaging department. We picked all of the project participants randomly with various engineering background (cybernetic, electrical, system mechanical/process, and mechanical). The survey uses a five point Likert scale and is evaluated by using the Net Promoter Score, e.g. strongly agree are the promoters, agree are passive and no opinion, disagree and strongly disagree are detractors. Hours absorbed associated with information finding: Only 10% of engineers absorb 30 minutes or less each week finding information. A normal engineer works 1650 hours/year (without overtime). Approx. 14000 hours are absorbed (wasted) in the company each year because there is little explicit knowledge available. According to the survey results, the majority of the engineers at Dresser-Rand Kongsberg absorb more than 2 working hours each week on finding relevant information in the current methods/tools and processes (Figure 5). Currently, there are around 200 employees in the company, where 132 of them are engineers. Assuming that the results below (Figure 5) hold for all the engineers in the company, we estimated hours absorbed per year for each group (Table 2). Figure 5: Survey feedback results on time absorption Table 2: Hours/year absorbed by each group finding information Group 1 2 3 4 Total Engineers (%) 10 20 40 30 Hours consumed per week (Median) 0,15 1,15 2,5 4 Engineers (Number of employees) 13 26 53 40 Working weeks (Per/year) 44 44 44 44 Total hours/year 9