Search results

Significant transitions in firms (e.g. outsourcing) may impact the relative importance of production and inventory assets, affecting the hierarchical separation of planning decisions. The purpose of this paper is to contribute to planning literature by investigating how the production system and the planning environment influence the performance difference between hierarchical and monolithic planning. Further, it seeks to reduce the prevailing theory-practice gap in tactical planning.

Through an action research study, a monolithic model integrating tactical production planning decisions, subject to upstream supply chain constraints, with strategic investments decisions was developed, tested and implemented in a global OEM. Using the developed model and a measure of the capital cost of production assets relative to the cost of holding inventory, it is numerically examined how the production system and planning environment influence the performance of hierarchical and monolithic planning.

The research demonstrates the potential of integrating decisions and reveals significant performance differences between hierarchical and monolithic planning for firms with low capital cost relative to inventory holding cost.

The findings suggest a fit between planning processes, the production system and planning environment. Future research should empirically validate the findings and propositions.

The paper combine capital investments and production planning decisions, which usually transpire at different hierarchical levels and on different time-horizons, and investigates the consequences of hierarchical separation through a real-life validated case and numerical analysis.

Some hierarchical approaches for production planning in a batch type manufacturing environment are described. In a single stage production system, three aggregation levels exist: types, families and items. The performance of a hierarchical system model is largely dependent on the methods of disaggregation at different levels. This paper reports on a study of hierarchical methods at the family disaggregation level and incorporates a simple modification to improve upon a heuristic proposed by Winters. Results indicate that even a very simple hierarchical planning approach can give a significant reduction in backorders in a production shop having severe capacity restriction.

A workstation‐based system for materials planning is intended to complement a host‐based materials‐planning system, thereby leading to a multi‐level system that combines fully detailed planning procedures with “aggregate” decision support capabilities. Planning objects as well as planning procedures are formulated within the relational database frame‐work. By that means, at execution time the database management system guarantees processing efficiency as well as consistency control. After a short characterisation of the state‐of‐the‐art of database utilisation in conventional materials planning, a set of requirements which have to be met by the proposed approach is formulated. Based on this, the suitability of the relational database model as a framework for multi‐stage materials planning is discussed. In particular, the integration of abstraction hierarchies is emphasised and hierarchical planning procedures adopted from artificial intelligence are integrated into the concept. Some examples adopted from a prototype show that, at least for simple planning problems, it is possible to achieve end‐user support at any level of detail when using a relational database system for materials planning.

The purpose of this study is to propose and formulate an integrated hierarchical production, and maintenance‐planning model.

The proposed model is formulated mathematically and tested for some hypothetical cases. A two‐level planning is proposed to address the hierarchical planning problem, i.e. aggregate planning and detailed planning. A preventive maintenance planning is integrated into the aggregate planning, while machine breakdowns, which require corrective maintenance actions, are investigated in the detailed planning. The proposed general preventive maintenance model is tested against cyclical preventive maintenance models for some cases, and for evaluating the performance of the models, in terms of costs, and service levels.

The proposed general preventive maintenance model gives a better solution in terms of cost than the cyclical maintenance model (i.e. 6 per cent less costly), if the maintenance planning is executed separately from the production planning. In terms of service level, however, both models perform equally well with average service levels equal to 97.6 per cent. The effect of tight capacity, long maintenance duration, and small machine parameters similarly tightens the capacity. In these cases, it is shown that a stable level of capacity is more beneficial to achieve a better service level, which is gained if the preventive maintenance actions are carried out monthly.

At the aggregate level, the proposed preventive maintenance model considers a non‐cyclical planning, which means that the preventive maintenance periods do not necessarily fall at equally distant times. The inventory movement constraints at the aggregate level decouple machines to operate independently; hence the detailed level problem can be solved separately for each machine. In a rolling horizon approach, only the first period of the aggregate plan is implemented and disaggregated into the production of items at the detailed level.

The paper proposes an integrated model of hierarchical production and maintenance planning. A general preventive maintenance is integrated into the aggregate planning, while machine breakdowns are investigated in the detailed planning. To the best of one's knowledge, such a hierarchical view of production planning and maintenance has not been addressed adequately.

Airdrop operation has become an important transportation mode due to its mobility and rapidity and mission planning is one of the critical steps in the preparation of an airdrop operation. The purpose of this paper is to propose an efficient mission planning method for airdrop operation using multiple vehicles.

A hierarchical mission planning method is proposed. According to the objectives of the action, the mission planning is divided into three planning levels to form the hierarchical structure and the constraints are distributed among them. By doing so, the proposed approach converts the original mission planning problem to a constrained optimization problem, which is solvable using existing mathematical methods.

On the basis of analysis, the mathematic models of three planning levels are established. Each level has its own optimization objective, taking part of constraints into account. The integrated mission scheme had been obtained step by step.

This paper systematically tackles the complicated multiple vehicles airdrop mission planning problem, and it provides a platform for optimizing the outcomes. The mathematical models established in this paper could apply in a variety of more complex mission scenarios.

This paper fulfils an urgent need to study how the advantages of airdrop operation can be maximized through planning airdrop mission schemes carefully.

Illustrates a two‐level hierarchical system structure for solving the production planning problems of a steel manufacturing system. The structure is basically a goal‐diffusion mechanism between two levels. At the lower level a goal programming problem is solved and at the higher level a multi‐objective dynamic program is used to derive an optimum aggregate production plan and provide optimal resource allocation.

The purpose of this paper is to develop a holistic operations planning framework for grocery retailing. The authors aim to identify, describe and structure coherent demand and supply chain (SC) planning problems in a comprehensive architecture.

The authors reviewed key literature on retail SC management and sales planning. This built a foundation for the development of an integrated operations planning framework. The findings were evaluated through discussions with retailers and communications with retail planners, including personal interviews with 28 leading European grocery retailers and with people in related positions from the consumer goods industry and consultancies.

The core of this paper is the development of a coherent demand and SC planning matrix. It demonstrates planning interdependencies and defines a framework for retail operations. The grocery planning framework integrates retail specifics, as well as hierarchical and sequential aspects of decision making. That is why this planning architecture also forms the foundation for research and development of advanced decision support systems.

Planning tasks are identified in interrelated planning modules permitting coordinated and decentralised decision making, which is necessary for operational and complexity reasons. The planning framework assists retail planners in understanding their decision problem from a comprehensive perspective. Better coordination of different modules and further development of retail‐tailored analytical models will improve planning quality.

This is the first paper that structures retail demand and SC planning questions coherently in one framework, matching demand and supply from a long‐ to short‐term perspective and from supplier to customer.

Several studies have addressed the use of four-dimensional (4D) building information modeling (BIM) for construction management. However, the automation of the processes for generating 4D models and their integrated use with Location-Based Planning and the Last Planner® System is not well discussed. Therefore, this paper aims to develop a method for automating the generation and use of 4D BIM models integrated with Location-Based Planning and Last Planner® System supporting project control cycles.

The research strategy adopted was Design Science Research. The automated method for using the 4D models was developed and refined in two residential building projects in Brazil, along with 31 meetings and involving 11 direct users. The assessment of the proposed method focuses on four constructs: the impact of process automation, the impact on the identification and assessment of site progress and the planning process, ease of adoption and utility of the proposed method.

The results of this paper indicated increased adherence between planned and executed through an automated method for using the 4D models. The established routines enabled automating the link between the planning levels and the three-dimensional (3D) model, providing a more agile and updated data source and achieving 92.8% of user satisfaction regarding the deadline and frequency of delivery of the 4D model reports. Moreover, this study identified the relationships between the processes of the method proposed and Digital Models.

The primary scientific value achieved in this study is creating a method for automating processes and simplifying steps for the generation and use of 4D BIM models in the production planning and control cycles during the construction phase.

A firm must plan its manufacturing activities at a variety of levels and operate these as a system. Aggregate planning is medium‐range capacity planning which typically covers a time horizon of anywhere from three to 18 months. The goal of aggregate planning is to achieve a production plan which will effectively utilize the organization′s resources to satisfy expected demand. Planners must make decisions on output rates, employment levels and changes, inventory levels and changes, back orders, and subcontracting. Aggregate planning determines not only the output levels planned but also the appropriate resource input mix to be used.

The purpose of this paper is to contribute to solving the complexity problem as increased complexity is a main reason why projects fail to reach their goals, and it is unclear what complexity is.

Conceptual development integrating theories of materiality, teleology, and complexity, decision-making theory, communication theory, coordination theory, and qualitative, quantitative and participatory approaches are used in this paper.

To understand complexity, it is necessary to develop a material-systemic process approach and to distinguish structured from unstructured complexity. The social actors construct a complex material-systemic process between themselves and nature to handle unwieldy outer nature. The material-systemic approach reveals how materiel life-world arenas are developed through increased complexity and specialization. Handling complexity is possible by materiality in general and structural material in special, the interplay between inner time (planning) and outer time (production), and between human subjects and an underlying coordination mechanism. It is a systematic organizational blockade that reproduces internal complexity as unstructured and incomprehensible complexity.

The practical models of organizing are tested to the highest degree in construction industry. It is a task to try and examine the models in other types of projects.

The paper offers a proposal to a theoretical solution to the complexity problem going back to the roots in Enlightenment and shows at the same time through practical models how increased complexity may be the most important productive force in future projects.