A decision support framework for Production Flow Coordination using Supply Chain Management practices, Ordering Systems and Modeling techniques

Transcription

1 CIO2015, 007, v1: A decision supp th International Conference on Industrial Engineering and Industrial Management XXI International Conference on Industrial Engineering and Operations Management International IIE Conference 2015 Aveiro, Portugal. July 6-8, 2015 A decision support framework for Production Flow Coordination using Supply Chain Management practices, Ordering Systems and Modeling techniques Abstract One of the greatest challenges faced by companies is flow coordination in its supply chain (SC). For such coordination, it can be found in the literature and practice the use of modeling techniques, ordering systems (OS) and practices in supply chain management (SCM). These, however, are not jointly used for coordinated operations in SC, admitting then a theoretic gap to be explored. In that way, this work has the objective to present a decision support framework for production flow coordination by combining the use of those mechanisms. For the development of this framework, a literature review about methodologies in production flow coordination in SC was made. The developed framework has purpose to assist managers in the decision making process about the practices and systems that are more suitable for each situation, thus obtaining the best coordination in its supply chain. We highlight that the project is still in progress and the framework is in phase of evaluation. Keywords: Supply Chain Coordination; Supply Chain Management; Ordering Systems; Modeling; Process Analysis 1 Introduction A major difficulty faced by companies is to manage a supply chain in an effective way and build relationships between suppliers and clients that allow a production system to obtain competitive advantages and achieve its desired performance objectives related to cost, quality, speed, flexibility and reliability (SLACK; CHAMBERS; JOHNSTON, 2007) or even timeliness, custom ability or suitability (GODINHO FILHO; FERNANDES, 2005). In the last decades, there has been an exponential growth of studies and researches related to supply chain management, both in academia and business world, with many advances in the development of new practices, whether they are

2 2 CIO2015, 007, v1: A decision supp... 2 new methodologies, tools or techniques. These set of practices are found in the current literature on studies related to Supply Chain Management (SCM). According to Mentzer et al. (2001), SCM can be defined as systemic and strategic coordination of the functions and traditional business tactics, through negotiations between functional areas within a particular company and through negotiations in the supply chain. The authors explain that the purpose of this coordination is to improve the performance of an individual company and the chain as a whole in the long run. Lambert (2004) describes eight essential processes for the SCM. They are: Customer Relationship Management (CRM), Supplier Relationship Management (SRM), Customer Service Management (CSM), Demand Management (DM), Order Fulfillment (OF), Manufacturing Flow Management (MFM), Product Development and Commercialization (PD&C) and Returns Management (RM). The SCM's aim is to improve operational efficiency, responsiveness and profitability of the firms and partners in the supply chain, achieving this goal through the development and implementation of models, which must adapt to each different scenario and consequently there is not a single model that captures all aspects of the processes of a supply chain (BADOLE et al, 2012). Such models can be developed using different techniques of Operations Research and can be classified as a deterministic model, stochastic or hybrid. According to Taha (2010), in Operations Research there is not a single technique to solve all mathematical models that may arise; it is the type and complexity that determine the nature of the solution method. Problems relating to the production flow coordination are not restricted to relationships between organizations in the supply chain; they may also occur in industrial plants during the production process. However, when it comes to problems in this scope, we find in the literature a variety of practices for planning, programming and control of production, which are known as Ordering Systems (OS), which can be production, services and/or purchase orders. These OS, according to Fernandes and Godinho Filho (2011), can be defined as systems that schedule or organize/explode the requirements in terms of components and materials, and/or control the emission/release of production, purchase and services orders, and/or program/sequence tasks on the machines. Among these OS, we can cite the following systems: kanban, drum-buffer-rope (DBR), constant work in process (CONWIP), materials requirements planning (MRP), period batch control (PBC), among others. Despite the widespread use of the OS for coordination within companies, there is strict implementation of these systems for the coordination of orders between suppliers and customers, and most of the time they do not get equivalent performance when compared to coordinated orders between machines within a plant. It is noteworthy that depending on the characteristics of products and markets and the specifics of the strategies of each company or supply chain, an OS is more suitable than another, or may even support a combined use.

3 CIO2015, 007, v1: A decision supp Flow coordination mechanisms are designed to manage products and information flows in supply chains, among which we can mention the Vendor Managed Inventory (VMI), Quick Response (QR), Collaborative Planning, Forecasting and Replenishment (CPFR) among others. Sahin and Robinson (2002) provide an extensive review of the literature on flow coordination of goods and information sharing in supply chains, classifying the literature based on the degree of information sharing and coordination. The objective of this study is to develop a process for analysis and support in the decision making process about implementing mechanisms for production flow coordination in supply chain using modeling techniques, SCM practices and OS. To reach this objective, a literature review was made on the conditions under which use of each SCM practice, each OS and each modeling technique is more suitable. Subsequently, a decision support framework to choose the best combined use of coordination mechanisms was elaborated. 2 Process analysis framework From the used methodology, was developed a framework that presents a detailed characterization process of relationship between supplier and customer for later decision making (supported by a set of criteria) for suitable production flow coordination mechanisms in supply chains and subsequently qualitative and quantitative assessment of the decision. Thus, through the use of this elaborated process, any supply chain may implement the methodology to meet their expected performance objectives. One of the challenges of production managers is to decide which practices to use to achieve flow coordination of production and materials in the supply chain. The developed process is presented as a useful tool to assist in decision making, impacting positively on companies competitiveness which make use of it. Thus, it was created a flowchart through a conceptual framework that consists of 11 steps to assist managers in coordinating the production flow of relationships between supplier and customer in a supply, as shown in Figure 1. Step 1: The first stage of this framework deals with the characterization of the relationships between agents in a supply chain (e.g. subcontractor, supplier, manufacturing, customers) and their characteristics with the rest of the chain. For more details, see Galasso, Mercé and Grabot (2009).

4 4 CIO2015, 007, v1: A decision supp... 4 Step 1: Analyze supply chain relationship s characteristics Step 2: Characterization of the production system and the chain relationship Step 3: Choose the modelling technique Step 4: Choose the Ordering System Step 5: Choose the Supply Chain Management practice Step 6: Analyze the consistency of combined alternatives Yes No Are there other alternatives? Alternatives present consistency? No Yes Step 7: Question about integration decisions in the supply chain Step 8: Analyze the decisions Step 9: Analysis relative to supply chain planning and implementation Step 10: Assessment for certification of the supply chain Step 11: Evaluate qualitatively and quantitatively the impact on the production flow coordination Fig. 1 Decision support framework Step 2: This step consists on the characterization of the production system, impacting the choice of which modeling technique, OS and SCM practices to be used. Examples of characterizations may be: item class (A, B or C), volume ratio range, degree of

5 CIO2015, 007, v1: A decision supp repeatability, stability demand level, demand predictability and flexibility, setup time, etc. Step 3: The modeling technique that is most appropriated for the company s scenario and strategy to achieve its optimization goal should be chosen in this step. Badole et al (2012) show several existing techniques and their various applications found in the literature. Step 4: You must select the most appropriate OS to the case. To this end, Godinho Filho and Fernandes (2011) present the set of conditions under which each OS are recommended. Step 5: In this step, the most appropriate SCM practice(s) to the case is (are) selected. Thus, Severino (2012) presents several practices used in supply chain management and their contribution to production flow coordination. Step 6: The analysis consist in verifying whether the modeling techniques, the OS and the SCM practices complement each other or if the use of one prevents the use of another in the proposal for the combined use. In this sense, this complementarity is evaluated and a planning of the implementation of the combined use is done, defining the role of each and how the operating mechanism establishes the production flow coordination. It is noteworthy that when doing this planning it should be verified the impacts on infrastructure, resources and in the current work routines situations. Such evaluations allow detecting possible resistance in terms of the use of the possibilities. In the event of incompatibility between the chosen alternatives, two situations can happen: if there are other possible alternative, its consistency will be analyzed; if there are no other alternative, the previous steps must be repeated to verify if the characterization was done correctly, in case there were any misunderstanding in the terms of the choice.

6 6 CIO2015, 007, v1: A decision supp... 6 Step 7: This step is to examine the types of waste in the supply chain, as shown by Liu et al (2013), identifying the behavior of integration decisions. Step 8: The analysis of the decisions is relevant to specify which situations will be evaluated in relation to production, transportation, distribution, demand and control of the product, analyzing how much they will influence the quality, quantity and adequacy of transport, point of sale and product demand scenarios. For deeper understanding, see van der Vorst, Tromp and van der Zee (2009). Step 9: Evaluation about the ideal (planned) state and the actual (executed) state in the supply chain, describing its different levels (strategy, design, planning and operations) so that the applied tools are updated, making a planning and detailing on the functional level of the operations, as seen in Ivanov (2010). Step 10: For the evaluation and certification of the supply chain, as shown in Acar, Kadipasaoglu and Schipperijn (2010), is necessary to run simulation models relating to transport, product type, quality inspections, use of optimization techniques for production, evaluate the influence of the location on the delivery of orders and if the forecast will influence product demand. Step 11: It is recommended to test or simulate the chosen formulated proposal that presented theoretical consistency. Among the simulation goals highlights the verification of the proposal applicability in the real case or if such proposal impacts in other relationships in the supply chain in case a single item was analyzed. After the simulation, it should be evaluated the impact of the elaborated proposal in the coordination of the production flow in the studied supply chain. Therefore, it is suggested to carry out qualitative and quantitative evaluations. For the qualitative assessment, it is recommended the use as reference the activities of the sub processes of Manufacturing Flow Management Process (MFMP) as sug-

7 CIO2015, 007, v1: A decision supp gested by Goldsby and García-Dastugue (2003). The authors state that to have a coordinated production flow in the supply chain some activities should be developed in the relationship between supplier and customer. In this way, it is analyzed if the activities of MFMP proposed by the authors are being accomplished by implementing the proposal suggested by this framework. In terms of quantitative evaluation, it is suggested the use of performance indicators that are suitable for the case in question as, for example, the approaches of Beamon (1999), Gunasekaran et al (2001) and the SCOR model, with the approaches of Stewart (1995) and Dreyer (2000). 3 Conclusions Nowadays the production managers develop solutions for production flow coordination in the relationships between suppliers and customers through their professional experience, using tools they had the opportunity to meet in their academic or professional career. However, this decision making is performed by trial and error and does not obtain optimum results. It is in this sense that a decision support framework is developed, providing a tool that helps achieving better production flow coordination in the supply chain with the combined use of modeling techniques, supply chain management practices and ordering systems. With such process, the manager knows the relationship between supplier and customer with more details, allowing through a set of criteria to define the mechanisms of production flow coordination that are more suitable for the case, performing qualitative and quantitative evaluations before implementing it. Thus, using such a framework, the decision making process increases the probability of successful with the choice. 4 References Acar Y, Kadipasaoglu S, Schipperijn P (2010) A decision support framework for global supply chain modelling: an assessment of the impact of demand, supply and lead-time uncertainties on performance, International Journal of Production Research, doi: / Badole CM, Jain DR, Rathore DA et al (2013). Research and opportunities in supply chain modeling: a review. International Journal of Supply Chain Management. Available via Exceling Tech. Cited 29 Jan 2015 Beamon B (1999) Measuring supply chain performance. International Journal of Operations & Production Management, doi: / Dreyer D (2000) Performance measurement: a practitioner s perspective. Supply Chain Management Review. Available via HighBeam Research. Cited 30 Jan 2015

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