agile

Due to the contradictions of lean and agile approaches and meanwhile, their synergy, choosing, combining, and implementing these approaches with specific goals, strategies, and limitations is a key challenge for supply chain managers. The current research aimed to develop a dynamic system for implementing lean and agile approaches in the supply chain.

 THEORETICAL FRAMEWORK:

Supply chain management includes the planning and management of all activities involved in the supply chain and is considered a vital factor in the competitiveness of organizations. Lean and agile approaches are among the popular approaches in supply chain management. Lean philosophy seeks to eliminate waste and reduce costs based on more output with fewer resources according to customers' needs. Governing lean thinking and principles in the value stream is called lean supply chain management. Quick response to changes in demand, in terms of volume and variety, is called agility. The concept of this approach refers to choosing the right strategy in conditions of uncertainty and providing products and services to customers at the right time and place. Empowering new competencies to respond quickly and effectively to the market is called agile supply chain management. These two approaches have different drivers, prerequisites, and strategies, and each one pursues a specific goal.

The present study is in the category of qualitative-quantitative research. Based on the stages of research in the conceptual development stage, the model is placed in the category of qualitative research. At this stage, by content analysis of the research background, factors affecting the selection of agile and lean approaches have been identified. This stage includes four main steps: problem definition, data collection, analysis, and presentation of the final model. In the quantitative stage, using the system dynamics method, using the factors obtained from the first stage and lean and agile strategies, a model has been presented to evaluate the performance and choose the appropriate strategies in different conditions. Causal models and state flow have been drawn and model evaluation tests, structure evaluation, and sensitivity analysis have been done to confirm the model validity. Finally, different scenarios have been simulated and analyzed in this model. The information required for modeling and simulating the model has been collected from the Yazd Rubber Industries Complex.

In the qualitative stage and after content analysis by reviewing articles and zigzag coding, 106 codes from 31 studies were identified as open codes. In this study, it was done. By repeatedly reviewing the identified primary codes and comparing them, the codes with common content and concepts were classified under one concept. In this way, 40 subgroups were extracted. Finally, these codes were classified into 17 groups and 4 general levels of environmental, organization-related, product-related, and functional factors. After extracting the influencing factors on the selection of lean and agile approaches, the flow model has been presented and evaluated in Vansim software. After obtaining the valid model, by changing different variables and scenario analysis, approaches have been analyzed in three different scenarios. A comparison of selected scenarios and policies for each condition shows that, as a strategic strategy, eliminating waste is a priority in all scenarios.

CONCLUSIONS & SUGGESTIONS:

The current research has theoretical and practical implications. This research is a response to the need for a systematic and comprehensive framework of vital factors in choosing appropriate agile and lean approaches. In this article, the knowledge available in the literature about the agile and lean approach in the supply chain is organized to develop a model for choosing appropriate approaches. On the other hand, organizations do not need fixed degrees of leanness or agility in different situations. The presented dynamic model can examine specific strategies of lean and agile approaches in different conditions and finally provide certain degrees of lean and agility. In the situation that in previous studies, the combination of these two approaches is usually discussed and less attention is paid to the effect of conditions on the level of leanness and agility. Although this study tried to present a dynamic model for choosing lean and agile strategies with a comprehensive look at all conditions, due to the existence of other approaches such as resilient and green, future studies may examine other effective factors and strategies to present a more comprehensive model.

This research explores the development of an agile-lean production model enhanced by blockchain technology specifically tailored for the jewelry and gold industry. The adoption of blockchain aims to tackle prevalent challenges such as intricate supply chains, diminished value addition, transparency deficiencies, and fraud risks. By leveraging blockchain’s capabilities, including immutable origin verification and automated smart contracts, this model seeks to revolutionize the industry. It promises significant improvements in process efficiency, waste reduction, and overall product quality.Blockchain’s potential to provide a transparent and tamper-proof record of transactions is particularly advantageous for verifying the authenticity and ethical sourcing of precious materials. This research emphasizes that successfully integrating this advanced model requires substantial capital investment and a strategic approach to human resource management, adept handling of legal challenges, and robust data security measures.Further, the study will explore the practical implementation of blockchain within various stages of the production process, assessing its impact on operational agility and lean manufacturing principles. By addressing these critical aspects, the research offers a comprehensive framework for the jewelry and gold industry to enhance its competitive edge and sustainability.

Accelerating the agility of production control systems in today's dynamic production environment is one of the challenges that many types of research have been conducted using multi-agent systems to improve it. The current models of these systems have shortcomings such as limited predictability, low reliability in the decision-making process, poor ability to understand and interpret the current state of the system, control with many limitations, and generally the existence of error-prone systems. In order to solve these problems, the current research presents a new methodology for multi-agent production control based on integration with ERP, which improves the capabilities of the system in the face of the above deficiencies. The research method employed in this study is qualitative, and developmental-applicative, aiming to enhance the integration of multi-agent production control systems with ERP. The objective is to improve the flow of material, production, and the quality of semi-finished products on the production line by considering the parameters that influence them. The key accomplishment of this research is the development of a reliable production control methodology that encompasses three components: a data exchange framework, tools, and implementation. These components are derived from existing ERP information systems that are functionally mature and designed based on best practices with a focus on maintenance, modification, and performance, aiming to minimize errors. The developed methodology offers a practical and agile solution for enhancing production control using an ERP system, with a lower implementation cost than the implementation of a commercial ERP system with a separate multi-agent system.

Given that each supply chain strategy has shortcomings, so the purpose of this study is to provide a model for the Police supply chain by combining lean, agile, resilience and green supply chain strategies in the form of LARG supply chain management in order to take advantage of the model's capabilities. The above approaches are simultaneous.

The present research is a qualitative in terms of purpose and was done using data foundation theory. The research sample includes 12 experts in the field of Logistics were selected based on the sampling logic of research in a purposeful manner and according to the saturation rule. Semi-structured interviews were used to collect data. Data collected during the interview process were analyzed by open, axial and selective coding process.

The results of the interview's qualitative data analysis, led to the presentation of Police hybrid supply chain model with five main categories and 46 sub-categories in the form of contextual conditions (eight categories), causal conditions (five categories), pivotal phenomenon (nine categories) strategies and actions (six categories) conditions The intervener (nine categories) the consequences (nine categories).

Based on the paradigm model, it can be concluded that a holistic view of supply chain preparation at Police support will lead to the optimal use of resources, time, place and optimization of the preparation process.

Large supply chains consist of lean, agile, flexible and green supply chains, which are one of the most widely used supply chain management chains in the world, which are used to improve the performance as well as increase the efficiency and effectiveness of the organization. The purpose of this study is to investigate and explain the implementation of large supply chain in the police force of Greater Tehran.

The statistical population of this study consists of 30 professors, commanders and managers of NAJA readiness and support, all of whom have collected information. The validity of the questionnaire was obtained by experts and its reliability was obtained by Cronbach's alpha test with a coefficient of 0.769. The study of dimensions, components, large supply chain indicators and their prioritization have been the questions of this research. The research method was exploratory, which was done in the form of library and field studies with the help of a researcher-made questionnaire. Descriptive statistical methods as well as confirmatory factor analysis were used to analyze the data.

The results of exploratory factor analysis show that the NAJA supply and support chain model includes five dimensions. These dimensions are: multiple management, integration, performance, productivity management and green management.

Principled and correct implementation of large supply chain benefits from a clean, flexible, green and agile supply chain. This is achieved by establishing a logical connection between the mentioned principles.

Although agile software development approaches are more effective, comparing to traditional approaches, the implicit risk management processes in those approaches are not sufficient to address project risks alone, and the use of explicit processes to manage risks is essential. On the other hand, traditional risk management methodologies seem to be in contrast with agile philosophy. This study aims to provide a tailored process model for risk management in agile software development projects. The qualitative study is carried out using the meta-synthesis method, Delphi method, and interpretive structural modeling.  The research is done by coding 28 scientific articles. The initial findings were observed by collecting the opinions of 12 experts. We used the Delphi method and interpretive structural modeling, to determine the interdependencies between the processes. Besides, finding a new "risk facilitator" role, alongside the project team, the study further led to the identification of eight process-steps in form of three process groups: "risk tailoring", "risk commitment" and "post risk", in line with the agile development projects' life cycle.