Amit Kumar Arya and Suraj Choudhary
This study aims to represent Kaizen implementation in a machine vice manufacturing company. Kaizen has shown tremendous impacts on the production techniques and lead times. A…
Abstract
Purpose
This study aims to represent Kaizen implementation in a machine vice manufacturing company. Kaizen has shown tremendous impacts on the production techniques and lead times. A large number of small-scale industries have shown their existence in India. It has been difficult for small industries to survive due to tough competition among them. All are facing problems like low production and poor-quality products.
Design/methodology/approach
The methodology applied to implement Kaizen in Indian small-scale industry. Fishbone diagrams have been used to represent cause and effects. The result has been shown as savings in terms of money and time.
Findings
Inventory access time is reduced up to 87 per cent and total distance travelled and total time taken by product is reduced up to 43.75 and 46.08 per cent, respectively. A habit to maintain a clean workplace has been developed in workers.
Research limitations/implications
ISO could be integrated with Kaizen for more improvements.
Practical implications
The paper should assist those practitioners and consultants who have the desire to understand a better way of Kaizen implementation in small-scale industries of India.
Originality/value
This paper yields lots of values for practitioners to understand the need, impacts and significance of Kaizen implementation in small-scale industries of India. Also, it bridges the gap between theory and practice of Kaizen implementation in real working conditions in Indian industries.
Details
Keywords
Roberto Cerchione, Piera Centobelli, Pierluigi Zerbino and Amitabh Anand
The evolution of Knowledge-Management (KM)-related literature has highlighted that Knowledge Management Systems (KMSs) have undergone massive changes in collaborative…
Abstract
Purpose
The evolution of Knowledge-Management (KM)-related literature has highlighted that Knowledge Management Systems (KMSs) have undergone massive changes in collaborative environments. Information-Systems-enabled KM seems to be the necessary response to the recent challenges posed by globalisation and technology dynamics to both large companies (LCs) and small and medium enterprises (SMEs).
Design/methodology/approach
This paper provides a systematic review about KMSs to offer an analytical overview of their role in supporting innovative forms of knowledge translation occurring in collaborative relationships. A sample of 129 papers was selected and analysed according to three perspectives: unit of analysis (LCs, SMEs), phases of the KM process (adoption, translation) and topic area (KM Practices, KM Tools, KMSs).
Findings
The findings highlight five literature gaps: (1) the role of KM practices supporting knowledge translation; (2) the impact of the alignment among KM practices, firm's complexity, dimension and culture on KM process; (3) the effect of KM tools on knowledge translation; (4) the variety of KMSs exploited in both LCs and SMEs; and (5) the alignment between organisational structure and information systems in KM context. Accordingly, 13 research questions were formulated.
Originality/value
The proposed research questions define a formal research agenda that could steer further research efforts about the KMS topic for improving the body of knowledge in the KM field. Scientific literature is currently lacking a contribution assessing the role of KMSs in supporting innovative forms of knowledge translation that occur in collaborative relationships.
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Keywords
Cemalettin Akdoğan, Tolga Özer and Yüksel Oğuz
Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of…
Abstract
Purpose
Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).
Design/methodology/approach
Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.
Findings
In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.
Originality/value
An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.