Towards a Diagnostic Instrument to Identify Improvement Opportunities for Quality Controlled Logistics in Agrifood Supply Chain Networks

 Western-European consumers have become not only more demanding on product availability in retail outlets but also on other food attributes such as quality, integrity, and safety. When (re)designing food supply-chain networks, from a logistics point of view, one has to consider these demands next to traditional efficiency and responsiveness requirements. The concept ‘quality controlled logistics’ (QCL) hypothesizes that if product quality in each step of the supply chain can be predicted in advance, goods flows can be controlled in a pro-active manner and better chain designs can be established resulting in higher product availability, constant quality, and less product losses. The paper discusses opportunities of using real-time product quality information for improvement of the design and management of ‘AgriFood Supply Chain Networks’, and presents a preliminary diagnostic instrument for assessment of ‘critical quality’ and ‘logistics control’ points in the supply chain network. Results of a tomato-chain case illustrate the added value of the QCL concept for identifying improvement opportunities in the supply chain as to increase both product availability and quality. Future research aims for the further development of the diagnostic instrument and the quantification of costs and benefits of QCL scenarios

Job profiling: How artificial intelligence supports the management of complexity induced by product variety

Firms and supply chains (SC) increasingly are forced to customise products and optimise processes since today’s markets are, on average, more demanding in terms of both costs and customer satisfaction. Generally, when product variety (PV) increases not only improves sales performance, since products offered better fit customers’ expectations, but also increases the complexity in SC processes management, rising operational costs. For that reason, accurate management of product diversity is a fundamental point for the brands' success, which is why it is going to be investigated in that project. Moreover, firms’ managers apply strategies to mitigate or accommodate this complexity, avoiding the customer satisfaction and cost trade-off to remain competitive and survive. However, we were wondering if it is enough. Artificial Intelligence (AI) has emerged to stay. Digitalisation era, data availability, and the improvement in computing power have boomed AI’s potential in improving systems, controlling processes, and tackling complexity. These strengths are suitable to help managers not only to tackle the complexity arising from PV but also to boost the supply chain performance (SCP

Optimal scope of supply chain network & operations design

The increasingly complex supply chain networks and operations call for the development of decision support systems and optimization techniques that take a holistic view of supply chain issues and provide support for integrated decision-making. The economic impacts of optimized supply chain are significant and that has attracted considerable research attention since the late 1990s. This doctoral thesis focuses on developing manageable and realistic optimization models for solving four contemporary and interrelated supply chain network and operations design problems. Each requires an integrated decision-making approach for advancing supply chain effectiveness and efficiency. The first model formulates the strategic robust downsizing of a global supply chain network, which requires an integrated decision-making on resource allocation and network reconfiguration, given certain financial constraints. The second model also looks at the strategic supply chain downsizing problem but extends the first model to include product portfolio selection as a downsizing decision. The third model concerns the redesign of a warranty distribution network, which requires an integrated decision-making on strategic network redesign and tactical recovery process redesign. The fourth model simultaneously determines the operational-level decisions on job assignment and process sequence in order to improve the total throughput of a production facility unit

SUPPLY NETWORK CONFIGURATION USING THE VALUE ENGINEERING BASED METHOD

Supply network configuration considers the whole business logistics to maximize the economic performance of an enterprise. It is a complex strategic decision problem that concerns the long-term organization of suppliers, production factories, distribution centers, and manufacturing resources, thus an efficient decision support is necessary. This paper proposes a decision support method for the supply network optimization. In this method, the business process of a supply chain is described by the Supply Chain Operations References (SCOR) models firstly. Then the value of business processes in the supply chain is evaluated using the Value Engineering (VE) methodology, wherein the processes are defined by function analysis with quantitative comparison to select key functions. And the concept of quality and robustness of Taguchi method is applied to evaluate the performance of different alternatives which are generated by key functions. A case application of global enterprise is elaborated. The results show that the proposed model can effectively optimize the supply network configuration

Impact of reverse logistics practices and competitiveness in medium and small textile sector companies in Lima metropolitan

En la ?ltima d?cada las empresas han incrementados sus esfuerzos para hacer m?s eficientes sus procesos y junto con la din?mica del mercado que presionan a las empresas a redise?ar y adaptar procesos a las nuevas tendencias de hacer negocios, es all? donde la log?stica de los procesos juegan un rol relevante y esencial para elevar el nivel de respuesta y competitividad de las empresas hacia el mercado, gracias a que la log?stica ofrece un Amplio rango de posibilidades para redise?ar y adaptar nuevos conceptos a la cadena de suministros. Por esta raz?n la log?stica inversa incluye nuevas pr?cticas de gesti?n como el reus?, redise?o, y reducci?n de mermas. Adem?s, estas pr?cticas mejoran el ciclo de vida de los productos ya que tiene una visi?n transversal desde la producci?n hasta el cliente y viceversa. Es por ello, el objetivo de esta investigaci?n es proveer nuevas herramientas a las PYMES para mejorar la competitividad en un mercado tan cambiante y din?mico como en el que vivimos. Finalmente, se busca facilitar pr?cticas espec?ficas de log?stica inversa que contribuyan a la toma de decisiones estrat?gicas de la empresa