## 1 Introduction  
Decision makers of organizations will encounter various integration problems during decision-making and troubleshooting processes [1] owing to the limitation in the development of a complex manufacturing system. Enterprises and firms should define relative frameworks to address the challenges of information imbalance and cognition bias posed by the evolution of internet of things (IoT) techniques and telecommunication technology. Several enterprise systems, such as product lifecycle management, manufacturing execution system (MES) and enterprise resource planning systems [2, 3], assist firms in achieving Industry 4.0 criteria by tackling integration issues. However, customers prefer specific customized functions rather than generalized functions to tackle the integration issues [4]. Most of the firms collect research and development (R&D) information or relevant business development datasets to analyze the requirements of customers to reduce rework costs associated with transferring various systems to the final phase. In contrast to the monolithic system, an application-specific microservice architecture can assist firms in expanding their services and defining new value propositions [5]. In this study, the service was modularized into several microservices with an integrated application programing interface (API) after adopting a microservice architecture. Furthermore, service providers can split or combine different applications based on the requirements of their customers (Figure 1). However,the storage cost, which is difficult to estimate, can be calculated by the volume of operations performed and applications stored [6]. The achievements on the level of system integration and requirement can be used as indicators of digitalization progress to identify the gaps and limitations in different systems [8]. Upstream and downstream firms can develop integrated strategies by alternating between the roles of service providers and customers for the benefit of information transparency. Service quality is always one of the crucial factors affecting the business development of a firm despite the challenges posed by market changes and business transformations [9]. Service-dominant (S-D) logic is a concept of combining services and individual business elements with product or process innovation to emphasize the value of cocreation [10]. The strategy of building a dynamic adjustment and coreated mechanism with business partners is crucial in handling business chaos. In this study, we modularized various services into several microservices to reduce and spread the operational risk. The proposed modularized structure stimulates the innovation process to effectively meet the distinct customer requirements within the market [10]. Firms can expand their business across different markets by integrating the recommendations of second or third parties. In addition to the specification and description language that are critical to the entire framework, the coreated features and microlevel service viewpoint assist the system by allowing self-moderation. Service quality can influence business performance directly or indirectly based on service orientation strategy and microservice architecture. However, invisible quality issues, which are related to system design, may damage goodwill [11]. Service quality indicators, such as reliability or different yield rate issues, are considered in the manufacturing industry. Various evaluation methodologies have been proposed under different scenarios owing to the rapid development of the digitalization applications [12]. The research question in this study is how corporations conduct service innovation through specific processes or approaches under complicated Industry 4.0 construction scenarios. We assessed the reliability of different system combinations to evaluate the manufacturing service quality [13]. In addition, combining different microservices with failure causal relationships and electronics domain knowledge supported firms in new business development [14].