Strategic ramp-up planning in automotive production networks

In many industries, the frequency of production ramp-ups has increased due to shorter product life cycles and increased product variety. Production often takes place at globally dispersed facilities for customers in multiple markets, for example, in the automotive industry. Therefore, ramp-up planning must be carried out for a network. The planning problem at hand is to simultaneously optimise the allocation of products of a common product platform to plants, the timing of ramp-ups and ramp-downs, ramp-up duration and shape of capacity and production and transportation volumes with respect to the net present value of the profit. We develop a hierarchical planning framework and place strategic ramp-up planning therein. We provide a mixed integer programming model for this planning problem. Following the example of a German car manufacturer in the premium segment, we conduct a numerical analysis to obtain insights into optimal ramp-up and ramp-down decisions. The results show that it could be beneficial to use both steep and flat ramp-up curves. The impact of flexibility in the choice of ramp-up slots and the number of ramp-up curves provided on the objective value is substantial. The strategic ramp-up planning model outperforms sequential planning approaches.     

Supply chain planning in the German automotive industry

Following the evolution in the computer industry, quite a lot of car manufacturers currently intend to move from a built-to-stock oriented production of standardized cars towards a customized built-to-order (BTO) production. In the premium segment of Germanys automotive industry, the share of customized BTO cars traditionally is comparatively high. Nevertheless, German car manufacturers have spent a lot of efforts in recent years to further increase this share in order to realize short delivery times, high delivery reliability and a fast responsiveness. Surprisingly, comprehensive overviews of the short- and mid-term planning landscape of car manufacturers cannot be found in the scientific literature. Thus, the first part of the paper discusses supply chain planning, as traditionally established in the premium segment of the German automotive industry, and reviews methods of Operations Research (OR) that are able to support the various planning tasks involved. In the second part, the major change in strategy, currently to be observed in the German automotive industry, is briefly summarized in order to derive its impacts for the planning system and for the respective planning methods. In this way, challenges for a future application of OR methods in the automotive industry can be identified.     

Strategic supply chain management issues in the automotive industry: an Australian perspective

The automotive manufacturing industry is an extremely competitive one. Many companies are focusing on their supply chains for sources of competitive advantage. This paper presents the findings of an exploratory study that examined contemporary issues related to supply chains in the Australian automotive manufacturing industry. Data from interviews with managers from vehicle manufacturers, component suppliers, peak industry bodies and government agencies enabled the articulation of 10 key issues. These issues were validated as being relevant to the industry by another group of managers from the industry. Review of these 10 issues showed that the relationships between the parties in supply chains are complex, and despite the success of the industry, there are a number of structural weaknesses. These issues, when taken individually, pose significant risks to the industry. When considered collectively, these risks are magnified several fold. This paper also presents research questions in the form of formal propositions associated with the 10 issues that need to be rigorously tested in order to assess the long-term viability and success of the industry. The issues that are raised can also be relevant to other industries with similar supply chain dynamics.     

The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.     

Allocation of manufacturers through internet-based collaboration for distributed process planning

The pursuit of lower cost, shorter time-to-market, and better quality has led to a shift toward global production in today's competitive business environment. This shift however, forces manufacturing enterprises to have separate design houses and manufacturing facilities. In general, design houses are located in the same regions as customers to enable them to respond to the rapidly changing demands of customers. By contrast, manufacturing facilities can be placed in regions in which production costs are lower. However, this physical and logical separation between designers and manufacturers (or between upstream manufacturers and downstream manufacturers) raises various integration issues. The present paper addresses two of these issues: the framework for representing the data necessary to communicate requirements and objectives of the designer, and the methodology for utilizing such data to optimize the business objectives related to production cost and quality. The proposed representation, collaboration framework, and methodology will enable design houses and manufacturing facilities to realize the benefits of global production and to accommodate the management of loosely integrated supply chains.     

Delphi study on supply chain flexibility

The flexibility literature is dominated by research on manufacturing flexibility. More recently, supply chain flexibility has been recognized as an important flexibility construct for meeting customer demand. An Internet-based Delphi study involving a group of expert practitioners is used to enumerate the characteristics, and the importance of those characteristics, in making a supply chain flexible. Expert opinion is one method for gathering information that can be used to develop a model of supply chain flexibility and provide a framework for future research.     

Algorithm for constructing a delivery-sequencing/inventory-allocation plan for supply chain control in the operational planning level

This paper aims to propose an algorithm to construct a delivery-sequencing/inventory-allocation plan used to control a supply chain in the operational planning level. The algorithm which is mainly based on the improving search technique begins by determining a suitable initial sequence of customer orders, allocating available inventory and determining inventory replenishment plan according to the sequence, calculating the interesting goals, and finally searching the appropriate sequence of customer orders using a proposed pairwise interchange technique. The sequence of the customer order is considered appropriate if it can simultaneously give most preferable two goals: minimizing the total penalties paid by the supply chain, and minimizing the average cost of fulfilling each product unit transferred to customers. The efficiency of the proposed algorithm is tested by the numerical experiments based on real data from a selected supply chain in Thailand, namely the food-ingredient industry. Statistical results show that the proposed algorithm significantly outperforms the current planning heuristics used in the industry and some other well-known heuristics.     

A strategic model for exact supply chain network design and its application to a global manufacturer

This paper presents a comprehensive model that captures significant strategic decisions involved in designing or redesigning high-performance supply chains from the perspective of the manufacturer. The problem considers deterministic demand by multiple clients, for multiple products, over the periods of a long-term horizon. The design decisions involve selection of suppliers, establishment or resizing of production facilities and distribution centres, possible subcontracting of related activities, and selection of transportation modes and routes. The problem is formulated by a Mixed Integer Linear Programming model. Its objective is to minimise the overall costs associated with procurement, production, inventory, warehousing, and transportation over the design horizon. Appropriate constraints model the complex relationships among the links of the supply chain. The proposed model has been applied to a large case study of a global manufacturing firm, providing valuable insights into the transformation of the firm’s current supply chain network, as well as into the potential of the proposed approach.     

Model for flexibility evaluation in manufacturing network strategic planning

In response to market pressures, manufacturers have adopted different approaches to provide flexibility regarding several aspects. In this paper, we suggest a model for the evaluation of the flexibility of the manufacturing supply chain, based on graph theory techniques. This model defines maximum excess demand that may be met using flexibility. Recourse to flexibility enablers is determined based on cost minimisation. Such enablers are volume flexibility, mix flexibility and safety stocks. The proposed model is solved using a two-step Mix Integer Linear Programme; the first step consists in defining maximum demand that may be met while the second step concerns minimising cost. The main benefit of our model is to deal with realistic problems in a rather short time. Therefore, it can be used in a wide ‘what-if’ design process. It means evaluating various contemplated flexibility configurations in multiple demand scenarios in order to choose the best option. It can be also used during operational supply chain planning in order to face to an unbalanced situation. This paper ends with a numerical example illustrating our model’s efficiency.     

Making supply chain design the rational differentiating characteristic of the OEMs

For more complex products that require customers to undertake learning in order to retrieve or realize the products’ true values, the product design and supply management decisions are different from those of less complex products. Nonetheless, in spite of the undeniable significance of coordinating decisions across product design and supply chain structures, we know very little about how to do so in practical ways. In this paper, we build on previous findings and offer a framework to enable the application of the supply chain structure design early in the new product introduction process. The proposed framework is based on a field study of the common practices in one of the major North American automakers, but we believe that it is widely applicable in other industries.     

A framework for collaborative planning and state-of-the-art

Inter-organizational supply chain management incurs the challenge to align the activities of all members which contribute to the value creation of a product or service offered to customers. In general, a supply chain faces the “problem” of information asymmetry, members having their own objectives and constraints which may be in conflict with those of the other members. Still, activities have to be aligned in such a way that the supply chain as a whole stays or becomes competitive while each member wins by cooperating. A number of collaborative planning schemes have been put forward in the last two decades with different assumptions and different areas of application. This paper intends to provide a framework and an overview on the state-of-the-art of collaborative planning. The criteria of the framework will allow us to position existing concepts and to identify areas where more research is needed. The focus of the literature reviewed here will be on model-based decision support at the operational planning level.     

Investigating the implications of extending synchronized sequencing in automotive supply chains: the case of suppliers in the European automotive sector

In recent years automakers have paid considerable attention to synchronizing supply chain material flow. Potential benefits associated with synchronization include stability in both demand and supply patterns, inventory reduction, elimination of demand amplification and better long-term planning. In major European production sites, the geographic proximity of suppliers to the vehicle assembly plants provided the motivation for examining the feasibility of extending the synchronized sequenced delivery of components upstream in the vehicle supply chain. The value stream used in the research concerned the seating systems at two major European production sites. The results of extending synchronized sequencing from the first to the second tier showed a reduction in demand amplification to negligible levels, achieved overall synchronization levels of 99–100% and considerably reduced overall pipeline inventory between the vehicle assembly plant and the second tier component supplier. The findings suggest how the geographic proximity of suppliers can be used to implement multi tier synchronized sequencing of components to improve supply chain performance. Based on the results of the study a series of recommendations are provided concerning the supply chain implications of multi tier synchronized sequencing.     

Mathematical model for warehouse design and product allocation

The two primary functions of a warehouse include (1) temporary storage and protection of goods and (2) providing value added services such as fulfilment of individual customer orders, packaging of goods, after sales services, repairs, testing, inspection and assembly. To perform the above functions, the warehouse is divided into several functional areas such as reserve storage area, forward (order collation) area and cross-docking. The paper presents a mathematical model and a heuristic algorithm that jointly determine product allocation to the functional areas in the warehouse as well as the size of each area using data readily available to a warehouse manager.     

Quantitative model for evaluating the quality of an automotive business process

One of the key issues to business process control is the identification of measurable process attributes. For manufacturing processes these are typically physical parameters of the process (e.g. temperature, set points) or physical attributes of the manufactured product (e.g. dimension, functional performance). However, for business processes the metrics are more abstract. The challenge has been to develop metrics that capture the contributing subtle and hard to measure factors for business process control. This paper presents an analytical model that uses the weights-of-evidence concept to convert answers to audit or self-assessment questions into a single numerical process quality index. This index is used to forecast process success or failure and monitor its performance from start to end. The application of the approach is illustrated with an automotive industry product development sub-process where the process performance metric is the field warranty data, i.e. incidents per thousand vehicles (IPTV). The analytical model converts process self-assessment (failure mode and effect analysis) questions into a single numeric process quality index. The validity of the model is reflected in the strength of the correlation between the index and the IPTV results. Also, in this paper a measure is developed for identifying critical process quality assessment questions. This measure quantifies the deviation in the automotive business process that should have more focus. The significance of the analytical model proposed in this research is that the project managers or quality assurance auditors may be able to use the metric to predict product quality at any point in the product development process.     

Aggregate production planning in the automotive industry with special consideration of workforce flexibility

We present a new mixed integer linear programming approach for the problem of aggregate production planning of flowshop production lines in the automotive industry. Our model integrates production capacity planning and workforce flexibility planning. In contrast to traditional approaches, it considers discrete capacity adaptations which originate from technical characteristics of assembly lines as well as from work regulations and shift planning. In particular, our approach takes change costs into account and explicitly represents a working time account via a linear approximation. A solution framework containing different primal heuristics and preprocessing techniques is embedded into a decision support system. Finally, we present an illustrative case study and computational results on problem instances of practically relevant complexity.     

Negotiation-based collaborative planning in divergent two-tier supply chains

Advanced Planning Systems are based on the principles of hierarchical planning, which—at least at the top level—grounds on centralized planning. However, central coordination requires access to all relevant information and the power to impose planning results on all organizational units. In consequence it can be realized only for parts of an inter-organizational supply chain, and the question arises whether there exist alternate ways to achieve coordination. In this paper we describe a non-hierarchical, negotiation-based process, which can be used to synchronize plans between independent partners of a two-tier supply chain consisting of one supplier and several buyers. Assuming that all partners generate plans based upon mathematical programming—as in most Advanced Planning Systems at the master planning level—we show how modified versions of these models can be utilized to support the negotiation process by evaluating given purchasing orders or supplies and by generating counter-proposals. Resulting is an iterative, negotiation-like scheme, which establishes and subsequently improves a consistent overall plan based on a limited exchange of information between the supply chain partners.     

A manufacturing network design model based on processor and worker capabilities

This paper presents an optimization methodology to design networks of manufacturing facilities producing several products under deterministic demand. The bill of materials and the operations for each product are taken into account through the use of a product-state graph. Starting from the current state of the manufacturing network, the approach considers a multi-period planning horizon. For each period it specifies the facilities to open within the set of current and potential facilities, the mission for each of the centres in the selected facilities, the equipment to be used for producing the goods, and the structure of the network. Taking human resource competencies into account, the approach selects the type of workers to use for executing the manufacturing tasks. The transfer of resources between plants is also considered. A multi-period mixed integer linear programming model is formulated, a solution method based on the addition of specialized cuts is proposed and computational results are presented.     

Requirements management: an enabler for concurrent engineering in the automotive industry

Defining and agreeing the product requirements is especially important when the design and manufacture of a system is part of an Extended Enterprise. To realize an all-inclusive concurrent engineering process, tools for the upstream design activities are needed. In practice, it is often difficult for the companies to have a shared understanding of what needs to be developed, and so specifications contain ambiguities in describing the product requirements. This paper clarifies the problem domain in the context of a complex product, designed and manufactured in a pan-national Extended Enterprise and serving a highly competitive market. The authors show how the challenge can be addressed through the application of ontology. A model of a requirements-management tool is proposed that will allow the various systems and associated levels of a product to be described and then shared through the supply chain. A prototype system is presented and illustrated through a case study from the automotive industry.     

Strategic network design for multi-zone truckload shipments

In recent years, the truckload trucking industry has faced a serious problem in retaining drivers. The primary reason for this problem is the very-long driver tour lengths that keep drivers on the road for extended time periods. In this paper, we present a mathematical model for a multi-zone dispatching method that addresses this issue. In addition to reducing driver tour lengths to desirable levels, the model captures important aspects of other practical problems via unique constraints that address the perspectives of both the truckload company and the customers. Using this model, we first provide insights into various aspects of the problem as well as the nature of the interaction among the problem components that pertain to these perspectives. We later develop a construction heuristic and a tabu search framework, which considers driver tour length constraints (a major determinant of driver turnover rate) to solve the model. We provide computational results illustrating the excellent performance of the proposed solution procedure.