Investigating the Integration of Industry 4.0 and Lean Principles on Supply Chain: A Multi-Perspective Systematic Literature Review

The development of digital technologies in all aspects of human life leads to increasing the necessity for investigating them in the Supply Chain (SC) as the main channel to provide products. Moreover, Lean principles, with the aim of reducing wastes, could be one of the main research streams in SC in recent years. Therefore, it is valuable to figure out the mutual effects of Lean principles and digital technologies as two growing areas in SC. Previous works did not pay attention to investigating this relationship at the SC level and were more focused on the production level. However, the present work addresses this issue by conducting a multi-perspective Systematic Literature Review (SLR). Additionally, in the present SLR, the impact of individual Industry 4.0 technologies in relation to Lean principles was investigated from various SC perspectives. The results reveal the necessity of studying single SC processes in Lean Digital SC. Moreover, the applicability of each technology should be illustrated to alleviate SC operational and organizational issues. The results provide useful insights about applying single digital technologies as well as a combination of them to each SC process to solve specific issues

Impacts of digital technologies on supply chain performance: a system dynamics approach

The advent of Industry 4.0 and associated digital technologies makes it possible to share information and access data real-time. Such a capability needs to be investigated in the Supply Chain Management (SCM) to study the joint impacts of digital technologies on transforming SC members’ behavior. In this paper, Cloud Computing, Internet of Things, and Big Data Analytics have been selected due to their relevant effects on real-time information sharing within different SC echelons rather than inside one echelon. Moreover, the implementation of these technologies in real SC requires high investments. Also, due to the increased complexity of the SC after applying these technologies, their impacts on SC behavior and performance should be determined precisely. This paper proposes simulation as a cost-effective and comprehensive method to investigate how digital technologies affect SC performance. A three echelon manufacturing SC has been simulated by using System Dynamics (SD) modeling under different scenarios in both traditional and digital SCM. The results reveal a significant improvement of SC performance, in terms of inventory level and cost as well as order fulfillment ratio, in digital SCs compared to traditional SCs. Future research will further develop the model by validating the simulation results with real cases from the industry

Performance assessment of healthcare warehouses: An empirical approach

Healthcare (HC) warehouses play a pivotal role in providing a satisfactory service level for hospitals. In fact, the warehouse performance significantly affects the treatment of patients by supplying drugs and other medical products in the right place at the right time with the right quantity and quality. Therefore, performance assessment of HC warehouses leads to making the right strategy for improving them. Current literature highlights a lack of approaches comparing and contrasting logistics performance in different HC warehouses. However, recognizing and categorizing warehouses based on their performance similarities offers the advantage of better managing them with the selection of proper fitting strategies. In this manner, the decisions would be made according to the specific characteristics of each warehouse group to improve efficiency. In the present study, key performance indicators for HC warehouses are extracted from literature and semi-structured interviews with HC logistics professionals. Using an empirical approach, the data related to the performance of several warehouse are collected from a set of Italian HC institutions. Afterwards, the statistical tool named cluster analysis is applied for the classification of the investigated warehouses based on their logistics behaviour. This results in a specific analysis of the current state of each cluster. The cluster analysis outcomes are verified based on some demand and flow indicators. The proposed approach may stimulate further research about comprehensive performance assessments of HC logistics systems. Additionally, it provides HC decision-makers with a methodology giving valuable insights for the development of integrated strategies based on the actual logistics characteristics of warehouses. Future research could be conducted by considering a more complete set of variables with different levels of contribution to the overall logistics performance. Finally, the presented approach will be further tested in multiple HC settings