Purpose of this paper:

Order picking remains the costliest and error-prone process in warehouses, while existing paperless picking systems still require frequent user interaction for quality control. This paper investigates the feasibility of a lightweight, picker-worn sensing approach that minimizes explicit interaction by automatically detecting grasping movements. The objective is to assess whether infrared (IR) camera–based grasp detection can reach Technology Readiness Level (TRL) 4, corresponding to component validation in a laboratory environment.

Design/methodology/approach:

The study follows a feasibility-study design grounded in the TRL framework. A Leap Motion Controller 2 (LMC2) IR stereo camera is used to capture finger joint data. A rule-based algorithm detects stable grasping movements based on temporal stability of pairwise fingertip distances, without relying on machine learning. Desktop laboratory experiments are conducted with objects of varying size, shape, surface properties, and deformability to evaluate the robustness of grasp detection under controlled conditions.

Findings:

The results show that stable grasping movements can be reliably detected using IR finger tracking for a range of objects, including deformable and glossy items, provided a minimum object size is met. The findings demonstrate that IR-based grasp detection is technically feasible at TRL 4 and can serve as a foundational building block for picker-worn sensing concepts in order picking. The study contributes empirical evidence to a research area where logistics-specific feasibility analyses are still scarce.

Value:

The paper contributes to logistics and human–technology interaction research by providing an empirically grounded feasibility assessment of IR-based grasp detection in an order-picking context. In contrast to infrastructure-heavy sensing environments and deep-learning-driven approaches, the study demonstrates the potential of a lightweight, rule-based solution that aligns with the flexibility and scalability requirements of warehouse operations. By explicitly situating the contribution within the TRL framework, the paper offers methodological clarity on early-stage evaluation of emerging picking technologies and helps bridge the gap between laboratory sensing research and applied logistics systems.

Research limitations/implications:

The experiments are limited to desktop laboratory conditions and focus exclusively on detecting grasping movements. Warehouse-specific factors such as storage racks, occlusion, dynamic workflows, and integration with storage-bin confirmation or quantity verification are beyond the scope of this study and remain subjects for future research at higher TRL levels.

Practical implications:

The results suggest that IR camera–based grasp detection can be integrated into wearable picking support systems to reduce manual confirmations and interaction effort. As a lightweight alternative to infrastructure-heavy sensing environments, the approach has potential to improve usability and acceptance of picking technologies, while maintaining flexibility and scalability in warehouse operations.

Purpose of the paper: This paper aims to quantitatively compare manual and automated material transfer and storage configurations in a semiconductor manufacturing line by applying an NPV-based economic framework and system-level performance analysis.

Design/methodology/approach: A baseline operator-based transport system with manual racks was compared with two automated alternatives integrating AS/RS with either AMR or OHT. Throughput and transport-resource indicators were measured under controlled conditions, and the results were monetized into hard and soft savings to compute Net Present Value (NPV)

Findings: Both automated configurations improved throughput compared with the manual baseline. While AMR and OHT delivered comparable throughput, they exhibited different transport execution characteristics and cost structures. NPV analysis confirmed the economic viability of automation and highlighted differences in the relative attractiveness of AMR- and OHT-based solutions

Value / Originality: This study provides an integrated techno-economic evaluation framework that links system-level intralogistics performance with financial outcomes. It offers rare quantitative evidence on the comparative impacts of AMR and OHT when coupled with AS/RS in semiconductor manufacturing environments.

Research limitations / implications: The analysis is based on a specific semiconductor production line and controlled assumptions (e.g., fixed outbound patterns and processing times). Future research should extend the framework to multi-line environments, stochastic demand conditions, and broader operational scenarios.

Practical implications: The results provide actionable decision support for semiconductor manufacturers selecting between floor-based AMR and overhead OHT transport strategies under space, cleanliness, and investment constraints. The proposed NPV-based approach can support capital investment planning for smart intralogistics upgrades.