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Integrated production/distribution planning in the supply chain: The Febal case study
Abstract and Figures
Purpose
The paper seeks to investigate empirically the criticalities of a production system constrained by distribution, in order to propose a model capable of integrating production and distribution planning for a simultaneous improvement in terms of efficiency and efficacy.
Design/methodology/approach
Starting from an overview of previous works about integrated analysis of a production‐distribution system, an exploratory case study in the Italian industry of modular kitchens has been used, with multiple levels of analysis and multiple data collection methods.
Findings
Three solutions for a better integration of production‐distribution systems are proposed; the solutions are characterized by increasing levels of benefits and complexity. The article focuses on the implementation of the less complex scenario, called “overlapping of selling areas”, proposing a series of algorithms used for the implementation of a software prototype.
Research limitations/implications
The case study has been chosen because it is representative of the assemble to delivery logic, where production is pulled and constrained by distribution, but it may not necessarily reflect all the firm's experiences in the furniture market.
Practical implications
The software prototype, developed on the basis of the proposed algorithms, allows a firm with production planning severely constrained by the distribution process to achieve better performance in terms of level of accomplishment in the delivery date promised and reduction of the lead time of delivery.
Originality/value
This paper proposes effective solutions for customer order‐driven‐production constrained by the distribution process, also offering practical help for managing and automatically assigning orders to transport carriers and for informing customers of the product's delivery date.
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... After the targets have been settled, it remains to implement the strategies, where the planning is organised in short, medium and long-term stages. According to this point of view, the hierarchy existing between such levels as strategic, tactical and operational is justified as a means of coordinating the organization's activities in order to ensure the its aims are achieved (Mintzberg, 2004). Porter (1996) argues that the decisions made by an organization both determine and reveal its objectives, intentions and goals, and that these invariably have to be followed by appropriate plans and policies. ...
... Lack of confidence in partnerships, as well as the need to aggregate value and reduce costs, are interrelated factors which are also involved in transport choices. There is a consensus among the companies studied concerning the use of their own transport and this finding is in agreement with the study carried out by Nonino & Panizzolo (2007) in the Italian furniture sector. This option is the result of lack of confidence in the service provided by third parties, especially that which is entrusted to independent truckers where the occurrence of late deliveries and damage to products are highlighted, when deliveries are shared with other companies. ...
This study evaluates the logistic strategies developed in Small and Medium-sized Enterprises (SMEs) as a response to their organizational structures and planning processes. A multiple case study was carried out in the second largest furniture cluster in Brazil. Based on theoretical models, it was found that the characteristics of a company’s organizational structure had an impact on planning. In the case of companies with a low level of family participation, this impact was intentional, whereas in the case of companies with strongly centralized owner control over decision-making, the impact was unplanned. However, the formal nature of planning does not guarantee that logistics will have strategic aims and, in all cases, it has a strictly reactive nature.
... With its significant strategic impact, AM is one of the technologies that greatly influence manufacturing industries [28], affecting not only operational strategy but also overall business strategy and sustainability perspectives. As Nonino et al. [29], and Khorram et al., [30], point out, AM is indeed changing business models, strategies and corporate operations, fostering numerous benefits in terms of sustainability in all its declinations. Specifically, referring to the field of economic sustainability, AM differs from traditional production in that it manages to circumvent the effect of economies of scale [31], as the unit cost of the products produced is not dependent on the quantity of production ( [32], [33]). ...
Increasing environmental concerns have prompted a worldwide emphasis on the implementation of novel or revitalised technologies that allow manufacturing companies to produce in an environmentally sustainable way while reducing resource, global warning, and waste generation. Additive Manufacturing (AM) technologies play a pivotal and revolutionary role in this particular industrial landscape. These new technologies are increasingly permeating industrial realities as they offer numerous advantages not only from an economic standpoint but also incorporate several potential sustainability benefits (e.g., reduced energy consumption and CO2 emissions, minimized waste production, lightweight product manufacturing through technological optimization, the possibility of using biodegradable and recycled materials, shorter supply chains through localized production, and reduced environmental impact). This study proposes a literature review on the topic of sustainable AM, focusing on the three aspects of sustainability (environmental, economic, and social). In particular, the analysis has revealed that AM positively influences the economic aspect of companies, as it allows for the reduction of processing waste, effectively transforming this into positive monetary value. Another relevant aspect is that these technologies enable the decentralization of manufacturing sites, meaning that production can be moved closer to the customer, thus reducing or eliminating transportation-related costs. While AM offers positive opportunities in these first two aspects, there is still limited research exploring its impact on social sustainability. Although AM has yet to radically transform industrial systems, there are early signs indicating that the characteristics of this advanced production process will lead to advancements in industrial sustainability.
... Several studies have also been conducted on various aspects of SCM. Most of these studies are on comparative analysis, conceptual development, increased performance through development of relationships, coordination and integration among the partners in the SC, factors affecting the quality of the SC, time management, production process for an effective SC, etc. (Bertolini et al. 2007;Bozarth, Blackhurst, and Handfield 2007;Eng 2005;Giannakis and Croom 2004;Halldorsson 2007;Kwon and Suh 2004;Nonino and Panizzolo 2007;Paulraj and Chen 2007;Prasad and Sounderpandian 2003;Sengupta, Heiser, and Cook 2006;Sila, Ebrahimpour, and Christiane 2006;Selldin and Olhager 2007;Sunhilde 2008;Sobhan 2003;Wu et al. 2004). A few studies have been conducted specifically on SCM in the clothing sector (Hunter and Valentino 1995;Christopher, Lowson, and Peck 2004;Nordås 2004;Knutsen 2004;Seuring, Goldbach, and Kopline 2004; of these studies have primarily dealt with ICT applications and the development of relationships amongst the members of the SC. ...
This study attempts to develop a model of improving competitiveness through analysing the supply chain (SC) of RMG industry in Bangladesh. The main objective of this study is to investigate the influence of external stakeholders’ of RMG SC to the demand side and supply side issues for improving competitiveness. Mixed method research is adopted in this study and data are analyzed by Partial Least Square-based Structural Equation Modelling. This study revealed that stakeholders have influence to improve competitiveness.
... ERP system is ability to manage multiple areas of a firm including sales and purchases, production planning and scheduling, process design, inventory management, and quality control (Gupta and Kohli, 2006). Nonino and Panizzolo (2007) commented that ERP leads to different benefits as an increase in productivity, a higher level of efficiency in the information flow, better warehouse management, and costs reduction. Managers have also reported that the integration between ERP systems and quality management is also important for managing customers and supplier relationships and managing the product and process in the best ways (Foster and Ogden, 2008). ...
... This emerging technology is changing companies' business models, strategies and operations, bringing huge benefits for their economic, social and environmental sustainability (Niaki and Nonino, 2018b). Regarding operations strategy, the actual and future expectation is boosting productivity through optimizing time, cost, quality and flexibility mostly in the new product development process, manufacturing and supply chain management (Nonino and Panizzolo, 2007). ...
Purpose
The purpose of this paper is to investigate additive manufacturing (AM) phenomenon extending previous research results by studying in-depth the economic sustainability of AM technology and bringing out the contextual factors that drive its superior performances in comparison with conventional manufacturing, and justify its adoption in rapid prototyping (RP) from an economic point of view.
Design/methodology/approach
Data have been collected through a worldwide survey. Respondents were from 105 companies adopting the technology from 23 countries worldwide.
Findings
The results of this research show that although AM-based prototyping leads to significant cost reduction, it is not as good as conventional manufacturing in terms of the profitability of investment. It also demonstrates how cost reduction depends on production volume and payback period depends on the types of material and scope of AM implementation after controlling for firm size and experience.
Research limitations/implications
The performance indicator is measured using a Likert scale; however, more reliable conclusion could be made by real amounts. The research also took into account the economic aspects of performance; however, to evaluate the AM technology more comprehensively, other performance measures such as those of social and environmental ones should be considered.
Practical implications
The paper provides insightful implications for the adoption of AM. In particular, it reveals the contingent performance of the technology in RP.
Originality/value
This paper contributes to expand the literature by demonstrating how different circumstances affect the performance of AM technologies for prototyping and by linking the operational and organizational factors with its performance.
In order to determine the impact caused by demand variations in the supply chain, and how capacity, inventory, process or workforce operational policies can mitigate this impact, and help management achieve a competitive chain in order delivery, a Discrete Events Simulation Model was developed to observe the behavior of the queues and a Simulation Models of Continuous Processes or Systems Dynamics, to test operational policies. Managing a Supply Chain represents an important challenge, especially considering the need to make it competitive, consequently, having a balanced supply chain configured allows better understanding the existing relationships between the operational policies and the underlying structure, and their link with the behavior dynamic system without creating incompatibilities. It was demonstrated in this study that the use of operational policies in the Supply Chains integrated by PyMES as tools to improve competitiveness in the delivery of orders and the convenience of applying these operational policies in a combined manner as a way to avoid imbalances in the system, such as: Accelerated growth in the level of pending orders that causes a deterioration in the credibility of the chain and consequently a decrease in orders. With this demonstration, one of the most important contributions of this work was achieved: Contribute to reduce the uncertainty in the decision making of the chain administrator, because it can quickly analyze which combination of operational policies is better is more effective in the face of a change on demand and before putting it into practice.
Sistemas, modelos y simulación, conforman en su conjunto la teoría, los métodos y las herramientas suficientes para que la nueva gerencia y/o la gerencia posmoderna hagan uso sin limitaciones de ellos, con la intención de reducir la incertidumbre y tomar decisiones apropiadas en pro del crecimiento de la organización.
Sistemas, modelos y simulación, conforman en su conjunto la teoría, los
métodos y las herramientas suficientes para que la nueva gerencia y/o la
gerencia posmoderna hagan uso sin limitaciones de ellos, con la intención de reducir la incertidumbre y tomar decisiones apropiadas en pro
del crecimiento de la organización.
Vale la pena recordar que con el término Teoría:
Se alude a un conjunto fundamental de proposiciones acerca del
funcionamiento del mundo, el cual se ha sometido a repetidas verificaciones y se ha ganado cierta confianza. Nuestra palabra Teoría deriva de la raíz griega theo-rós, que significa espectador. Ella
proviene de la misma raíz que la palabra teatro. Los seres humanos
inventamos teorías por las mismas razones por las cuales hemos inventado el teatro: para escenificar en un espacio público ideas que
nos ayuden a comprender el mundo (Senge, 1995: 30).
El proceso por el cual los investigadores generan nuevas teorías está
lleno de pasión, de imaginación y de la alegría de observar algo nuevo
en el mundo. Como ha dicho Buckminster Fuller: la ciencia consiste en
poner orden los datos de nuestra experiencia. Partiendo de este hecho, las
nuevas teorías penetran en el mundo de los asuntos prácticos cuando se
traducen en métodos y herramientas. Método deriva del griego méthodos
que significa buscar objetivos específicos. Esta palabra evolucionó hasta
cobrar su significado actual: un conjunto de procedimientos y técnicas
sistemáticas para abordar asuntos y problemas determinados, por ejemplo, la Dinámica de Sistemas.
En la misma línea, las herramientas aluden a un objeto, pero aquí se
aplica este concepto por extensión a todo utensilio mental que permita
realizar una tarea, como es el caso de los Círculos Causales que existen
19
para modelar y simular otras herramientas que de alguna manera someten la Teoría de Sistemas a verificaciones prácticas, lo cual permite a la
vez el afinamiento de la teoría. Este ciclo continuo -creación de teorías,
desarrollo y aplicación de métodos y herramientas prácticas basadas en
las teorías, obtención de nuevas perspectivas que mejoran las teorías- es
el motor que impulsa el crecimiento en ciencia y tecnología (Senge, 1995:
32), es decir, Círculos Causales de Crecimiento y de Estabilización.
Por otro lado, el Pensamiento Sistémico y las herramientas de los Arquetipos Sistémicos se basan precisamente en una metodología general,
desarrollada por el Massachusetts Institute of Technology (MIT) en los
últimos cincuenta años, llamada, como ya se mencionó, Dinámica de Sistemas, y procura entender cómo la estructura de retroalimentación de los
sistemas complejos genera pautas de conducta, o sea que la estructura hace
la conducta.
La metodología se basa a su vez en la Teoría de los Sistemas Complejos de Retroalimentación que se ha desarrollado en ingeniería en el
último siglo y medio. Una parte de la teoría describe que los sistemas
complejos suponen procesos de retroalimentación de refuerzo y equilibrio. (Senge, 1995: 35)
En este trabajo, se presenta una serie de pasos, o sea una metodología, para desarrollar modelos causales con o sin la ayuda de arquetipos
y modelos informáticos, con el fin de simular escenarios en atención al
ajuste de políticas aplicables a cualquier organización de cualquier sector,
sea Agroindustria, Manufactura, Servicios y Conocimientos Estas políticas generales abarcan operaciones de proceso, capacidad, inventario,
fuerza de trabajo, calidad y otras que pudiesen aparecer.
En la parte final se muestran algunos modelos desarrollados a lo largo de nuestras investigaciones, en las cuales se ha utilizado Dinámica de
Sistemas.
This paper proposes a new paradigm for tactical demand chain planning (DCP), called robust planning, based on risk assessment of the supply and demand chain. The concepts of supply chain management (SCM), and its extension demand chain management (DCM), have been at the center of much recent research. One of the reasons for this is that, over the last years, a significant number of information systems have emerged, which claim to support the concept. The paper argues that these systems mostly adopt a myopic view of planning, based on pure deterministic planning methods. It demonstrates that such an approach fails to coop with the considerable uncertainty of the planning information. The proposed robust planning paradigm is then introduced and its impact explained, using the well‐known example of the beer game. It holds the promise of reducing the number of re‐planning cycles, through a better characterization of the expected service level performance over a medium planning horizon. Finally, a case study will show the value of robust planning in a European chemical enterprise.
Recently, there have been numerous calls for more empirical field‐based research to be conducted in operations management (OM). Knowledge of how operations systems work can be enhanced significantly through contact with the “real‐world” conditions that OM models seek to describe. Case study research is a primary means of exploring field conditions but is an unfamiliar methodology for many in OM. Moreover, the case study method is viewed with scepticism by those who consider it to be a weak form of research, one that lacks rigor and objectivity.
Here, we offer an introduction to the case study method for OM researchers who may have little background in field based research. We provide an outline of the procedure and cite some excellent sources that cover case study design, data analysis and the philosophical rationale for the methodology. We also identify some recent examples of OM case studies that illustrate our points. We then contrast the various uses for case study research and their different design and theory requirements. An appendix provides a listing of case studies that have appeared in some OM journals in recent years, classifying the studies by their research purpose.
However, regardless of their purposes, case study research need to be conducted in a manner that assures maximum measurement reliability and theory validity. We describe some of the steps that must be taken to ensure that a study is as rigorous as possible. We also argue that, properly conducted, a case study is a truly scientific research approach. We conclude by pointing out some areas of OM research where case studies might be particularly valuable.
Case and field research studies continue to be rarely published in operations management journals, in spite of increased interest in reporting such types of studies and results. This paper documents the advantages and rigor of case/field research and argues that these methods are preferred to the more traditional rationalist methods of optimization, simulation, and statistical modeling for building new operations management theories. In the process of describing the constructs of inference and generalizability with reference to case research, we find the existing definitions inadequate and thus extend and refine them to better discriminate between alternate research methodologies. We also elaborate on methods for increasing the generalizability of both rationalist and case/field research studies. A major conclusion is that these alternate research methods are not mutually exclusive and, if combined, can offer greater potential for enhancing new theories than either method alone.
- This paper describes the process of inducting theory using case studies from specifying the research questions to reaching closure. Some features of the process, such as problem definition and construct validation, are similar to hypothesis-testing research. Others, such as within-case analysis and replication logic, are unique to the inductive, case-oriented process. Overall, the process described here is highly iterative and tightly linked to data. This research approach is especially appropriate in new topic areas. The resultant theory is often novel, testable, and empirically valid. Finally, framebreaking insights, the tests of good theory (e.g., parsimony, logical coherence), and convincing grounding in the evidence are the key criteria for evaluating this type of research.
Early MRP-systems were developed without recognition of the Master Production Scheduling function. Material Requirements Planning (to become termed later as MRP I) was considered a deterministic mechanism, translating a known demand into planned orders for components and subassemblies-in such a way, that nearly all inventory could be avoided. The question, whether the demand was really known was not posed; the demand had to be known. This idea was reflected in standard software packages for MRP I, where no decision-support systems for master production scheduling were provided (for example PICS [6]).
We present a general framework for modeling routing problems based on formulating them as a traditional location problem called the Capacitated Concentrator Location Problem. We apply this framework to two classical routing problems: the Capacitated Vehicle Routing Problem and Inventory-Routing Problem. In the former case, the heuristic is proven to be asymptotically optimal for any distribution of customer demands and locations. Computational experiments show that the heuristic performs well for both problems and in most cases outperforms all published heuristics on a set of standard test problems. 1 Introduction Vehicle routing problems have received much attention in recent years due to the increased importance of determining efficient distribution strategies to reduce operational costs in distribution systems. A typical routing problem consists of a fleet of vehicles located at a central depot or warehouse that must be scheduled to provide some type of service to customers geograp...