Development of an Intelligent Digital Dashboard Using Design Thinking to Improve Production Visibility in Automotive Aftermarket Manufacturing - Ratna Sari Dewi; Drajat Drajat; Mahendra Wardhana (Universitas Dharma Wacana, 2026)
The increasing complexity of automotive aftermarket manufacturing requires companies to improve production visibility and decision-making through digital transformation. However, many manufacturers still depend on fragmented information systems, manual data recording, and limited real-time monitoring, leading to production delays, inaccurate material planning, and inefficient delivery performance. This study aims to develop an intelligent digital dashboard that improves production visibility using a user-centered approach based on the Design Thinking methodology.A qualitative case study was conducted at PT Adyawinsa Stamping Industries, an automotive component manufacturer. The Design Thinking framework, consisting of the Empathize, Define, Ideate, Prototype, Test, and Reflect stages, was applied to identify user needs, design an interactive dashboard, and evaluate its usability. Data were collected through observations, semi-structured interviews, workshops, document analysis, and usability testing involving production managers, operators, administrators, marketing staff, purchasing personnel, and information technology specialists. The developed dashboard integrates purchase order management, material availability, production progress, barcode-based work-in-process monitoring, delivery scheduling, and key performance indicator visualization into a single digital platform. The evaluation results show that the dashboard improves production visibility, information transparency, communication between departments, and production monitoring efficiency. It also supports faster and more accurate managerial decision-making by providing real-time production information. The findings demonstrate that combining Design Thinking with intelligent dashboard development offers an effective strategy for digital transformation in automotive aftermarket manufacturing. This research contributes to the development of practical, user-centered decision support systems that enhance operational performance and support Industry 4.0 implementation in manufacturing environments.