Technical Debt Identification and assessment in mechatronic systems applying indicators, patterns, and metrics - TDebituM

技术决策在短期内是有利的，但从长期来看却被证明是不利和昂贵的，因为它们的后果、影响和纠正措施的范围根本没有被考虑或被低估。这种现象被描述为软件系统领域的技术债务(TD)。关于机电一体化中更精确的自动化生产系统中TD的少数研究结果已经表明，与软件和嵌入式系统相比，首先，即使在应用软件及其平台中，也可以在所有三个机电学科中观察到新的附加TD类型，第二种TD类型是由于机电一体化的跨学科产生的，第三种TD类型是由于机电一体化系统的附加生命周期阶段。因此，TDebituM系统地分析了自动化生产系统中的机电一体化系统中的TD，更准确地说，机器和工厂制造，以及汽车行业中代表德国两个关键行业的机电产品，例如，调查以下研究问题：-与软件系统相比，可以识别哪些附加TD类型和子类型在机电系统生命周期的哪个阶段，它们发生的频率、原因和后果是什么？-在机械、电气工程以及应用软件及其平台中，可以为这样的机电TD或TD确定哪些指标、模式和指标？-可以观察到哪些源效应关系？使用德国和选定的国际工业公司的专家访谈，收集上述机电系统领域的TD事件。统计分析方法被用来检查分类的TD属性的发生、关键程度、重要性和相关性。识别的静态TD模式和序列被用来定量地定义TD度量。与不同领域的专家以迭代的方式开发的概念有助于可视化地了解TD及其在公司本身和供应链中的沟通，并与TD进行互动。TDebituM通过与个别专家以及至少10%的受访公司的焦点小组一起对结果进行评估，证明了结果的有效性。TDebituM通过考虑机电一体化学科、生命周期中的其他阶段、跨学科依赖关系以及由此产生的问题转移，探索了有意并尽可能无意的TD事件，并扩展了软件和嵌入式系统的现有知识。及早发现潜在的TD事件，并透明地展示相互关系、维度和风险，支持复杂机电系统整个生命周期的技术决策过程，并为所有进一步的TD管理活动奠定基础。

Technical decisions that are expedient in the short-term, yet prove as disadvantageous and expensive in the long-term are often made, as their range of consequences, impact, and corrective measures are not considered at all or underestimated. This phenomenon is described as Technical Debt (TD) in the domain of software systems. The few research results on TD in mechatronics more precisely automated production systems already show in comparison to software and embedded systems that at first new additional TD types can be observed in all of the three mechatronic disciplines even in application software and its platforms, second TD types that result from the interdisciplinarity of mechatronics and third from the additional life cycle phases of mechatronic systems.TDebituM therefore systematically analysis TD in mechatronic systems for both automated production systems, more precisely machine and plant manufacturing, and mechatronic products in the automotive industry representing the two German key industries investigating, for example, the following research questions: - Which additional TD types and subtypes can be identified in comparison to software systems, in which phase of the mechatronic systems’ life cycle and with which frequencies, causes, and consequences do they occur?- Which indicators, patterns, and metrics can be identified for such mechatronic TD or TD in mechanical, electrical engineering as well as application software and its platforms?- Which source effect relations can be observed?Using expert interviews in German and selected international industrial companies, TD incidents in the field of mechatronic systems as mentioned above are collected. Statistical analysis methods are applied to examine the classified TD properties for occurrence, criticality, significance, and correlation. Identified static TD patterns and sequences are used to define TD metrics quantitatively. A concept developed in an iterative way with experts of different foci serves the visualization of, and interaction with TD and its communication in the company itself as well as in its supply chain. The validity of the results is proven by an evaluation of the results with individual experts as well as focus groups in at least 10% of the interviewed companies.TDebituM explores the deliberate and, as far as possible, the inadvertent TD incidents and extends the existing knowledge for software and embedded systems by considering the mechatronic disciplines, additional phases in the life cycle, interdisciplinary dependencies, and the resulting problem shifting. Early detection of potential TD incidents and a transparent presentation of the interrelationships, dimensions, and risks support the technical decision-making process along the life cycle of complex mechatronic systems and lay the foundation for all further TD management activities.