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The purpose of this paper is to provide comprehensive information on preventive maintenance (PM) planning and methods used in the industry in order to achieve an effective maintenance system.

The literature review is organized in a way that provides the general overview of the researches done in the PM. This paper discusses the literatures that had been reviewed on four main topics, which are the holistic view of maintenance policies, PM planning, PM planning concept and PM planning-based in developing optimal planning in executing PM actions.

PM policy is one of the original proactive techniques that has been used since the start of researches on maintenance system. Review of the methods presented in this paper shows that most researches analyse effectiveness using artificial intelligence, simulation, mathematical formulation, matrix formation, critical analysis and multi-criteria method. While in practice, PM activities were either planned based on cost, time or failure. Research trends on planning and methods for PM show that the variation of approaches used over the year from early 1990s until today.

Research about PM is known to be extensively conducted and majority of companies applied the policy in their production line. However, most analysis and method suggested in published literatures were done based on mathematical computation rather than focussing on solution to real problems in the industry. This normally would lead to the problems in understanding by the practitioner. Therefore, this paper presented researches on PM planning and suggested on the methods that are practical, simple and effective for application in the real industry.

The originality of this paper comes from its detail analysis of PM planning in term of its research focus and also direction for application. Extensive reviews on the methods adopted in relation to PM planning based on the planning-based such as cost-based, time-based and failure-based were also provided.

The paper seeks to describe the state‐of‐the‐art, reasons for selecting various material planning methods, and modes of applying methods for initiating inventory replenishment of purchased items. It also identifies trends from 1993 to 2005.

Empirical survey data are collected from Swedish manufacturing companies in 1993, 1999 and 2005. The MRP, re‐order point, fixed interval ordering, run‐out time, and Kanban methods are studied.

MRP is the most commonly used method and its position has strengthened since 1993. A common way of determining parameters such as order quantities and safety stocks is to use judgment and experience. Parameters used in material planning methods are reviewed relatively infrequently. The planning frequency has increased, with daily planning now being typical.

The major limitation is that different data collection techniques were used in 1993 compared with 1999 and 2005. An important research implication is that the state‐of‐the‐art applications differ from theoretically appropriate application modes. The trends are towards less appropriate modes among the most widespread applications.

The frequency of reviewing planning variables is relatively low in industry, and should in most situations be increased. The paper implies that more user‐friendly software applications need to be developed and implemented. It could serve as guidelines when designing and developing training and education programs and function as a benchmark.

The paper provides a longitudinal state‐of‐the‐art description of materials planning usage and identifies application modes with positive and negative performance impact.

The implementation and control processes of project planning and scheduling involve a wide range of methods and tools. Despite the development and modification and integration of the project management theory with newer scheduling approaches in particular, practitioners’ views on the efficiency and effectiveness of these methods and tools differ. This situation can be attributed in part to a lack of understanding of the most appropriate basis for implementing these methods and tools. This study, therefore, aims to overcome this deficiency by conceptualizing and adopting a taxonomy of planning and scheduling methods.

The study is based on a review and discourse analysis of the literature covering a large number of theoretical and empirical studies. The underlying theories of various planning and scheduling methods were analyzed with respect to the taxonomy criteria adopted in the study.

Using the taxonomy, the key characteristics of planning and scheduling methods considered in this study were identified and interpreted. These included concepts and theories; key features; suitability and usability; and benefits and limitations. Overall, the findings suggest that project managers should consider taxonomy as a support tool for selecting and prioritizing the most appropriate method or combination of methods for managing their projects. Recommendations include the need for more advanced or multi-dimensional taxonomies to cope with the diversity of project type and size.

The results of the study allow project managers to improve their current practices by utilizing taxonomy when considering the implementation of planning and scheduling methods. Moreover, taxonomy can be considered as a tool to promote learning on the part of those less experienced in planning and scheduling. Taxonomy can be considered as an initial platform for further research in this area.

The purpose of this paper is to provide a comprehensive overview of literature and methods that can be used for deconstruction project planning of buildings. Furthermore, shortcomings of the identified planning methods are presented and research gaps are identified.

Requirements to consider for the planning of deconstruction projects are defined, to help in the classification of planning methods. With the help of these requirements, in a detailed literature review strategic and operational planning methods for deconstruction projects are investigated and discussed. Requirements which are not met by any of the identified planning methods can be interpreted as research and/or documentation gaps.

On the one hand, the literature review shows that recent approaches deal with planning methods for deterministic time and resource scheduling. Furthermore, project costs can be well planned by several methods. On the other hand, the literature review reveals that recent approaches mostly do not consider risks and uncertainties, environmental hazards or specific safety issues. A major shortcoming is that applied planning methods can only calculate up to a specific level of detail, e.g. with a limited number of activities, due to a very high computational effort in solving such project planning problems exactly.

To the authors’ knowledge, this is the first study that provides an overview of literature and methods for the deconstruction project planning of buildings and it is also the first study that unveils research gaps for future research. Furthermore, the classified planning methods assist in identifying suitable methods for the planning of future deconstruction projects.

The applicability of manufacturing planning and control methods differs between environments. This paper explains the fit between the planning environment and material and capacity planning on the detailed material planning and shop‐floor planning levels. The study is based on a conceptual discussion and a survey of 84 Swedish manufacturing companies. Results show the use of planning methods and their levels of user satisfaction in complex customer order production, configure to order production, batch production of standardized products and repetitive mass production, respectively.

Making decisions on production and maintenance separately, as is often done in practice and research literature, may not result in overall optimization. This paper aims to propose a joint method that better integrates production planning and maintenance at the tactical level. The potential of improving the performance of the classic planning method is also explored.

An integrated production planning and maintenance model is proposed. The production capacity losses resulted from both preventive and corrective maintenance activities are considered. Meanwhile, the reliability deterioration of the machine is considered to be operation dependent. An iterative approach is presented to find a solution for the nonlinear model through iteratively solving a sequence of mixed integer linear programming instances, accompanied by modification of some parameters prior to each iteration. Computational experiments are conducted to evaluate the performance of the proposed method compared with three other methods, including two methods based on separate planning and one integrated model.

The superiority of the proposed method compared with all the other three methods is demonstrated. Thus, the values of both integrated planning and considering operation-dependent failures are testified. The advantage of the proposed method is highlighted in the cases of high capacity utilization, long maintenance durations and low maintenance costs. The performance of the two methods based on separate planning is sensitive to the system utilization, and when utilization is high, the one with an availability-sensitive objective function defined for the maintenance problem performs better.

Few studies have been carried out to integrate decisions on production lot and maintenance. Their considerations are either incomplete or not realistic enough. A more comprehensive and realistic integrated model is proposed in this paper, along with an iterative solution algorithm for it. A potential way to improve the performance of the classic planning method with its simplicity preserved is also presented.

The purpose of this paper is to show how collaborative information technology (IT) tools and a crowdsourcing model can be leveraged for the purpose of strategic planning. To achieve this objective, a formal method of open strategic planning (OSP) is proposed.

Based on a review of the literature a set of activities, stakeholders, and governing rules are identified in the form of an OSP method. The proposed planning method is implemented in a case study of strategic planning in an Australian university. Observations by the research team, and archival records were used to ascertain the relevance of the used method.

A method for OSP is presented and assessed. The method contains four phases: pre-planning, idea submission, idea refinement, and plan development. These phases cover the activities required from conceptualization to preparing and publishing the strategic plan. The findings clarify how the principles of OSP helped the organization to include more stakeholders and provided the opportunity to make the planning process transparent through use of a collaborative IT tool.

The study provides managers and planning consultants with detailed guidelines to implement the concept of open strategy.

This study is among the few to propose a method for OSP based on empirical research. The study also shows how collaborative IT tools can be used for high-level organizational tasks such as strategic planning.

This chapter explores the significance and implementation of family planning practices, emphasizing their vital role in enhancing reproductive health outcomes. This chapter conducts an in-depth examination of family planning practices within marginalized communities in Bangladesh, shedding light on the unique challenges and opportunities faced by these populations. By uncovering the nuances of family planning practices in marginalized contexts, this chapter underscores the need for tailored and culturally sensitive family planning programs. It advocates for program designs that facilitate the effective adoption of family planning practices among marginalized communities, ultimately promoting better reproductive health outcomes. Furthermore, this chapter highlights the importance of empowerment strategies in reaching and engaging marginalized communities. Through practice enhancement initiatives, it seeks to empower marginalized populations with the knowledge and resources necessary to make informed decisions about family planning, thereby contributing to improved reproductive health and overall well-being.

Computer aided process planning (CAPP) is generally acknowledged as a significant activity to achieve computer‐integrated manufacturing (CIM). In coping with the dynamic changes in the modern manufacturing environment, the awareness of developing intelligent CAPP systems has to be raised, in an attempt to generate more successful implementations of intelligent manufacturing systems. In this paper, the architecture of a hybrid intelligent inference model for implementing the intelligent CAPP system is developed. The detailed structure for such a model is also constructed. The establishment of the hybrid intelligent inference model will enable the CAPP system to adapt automatically to the dynamic manufacturing environment, with a view to the ultimate realization of full implementation of intelligent manufacturing systems in enterprises.

This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point.

Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%–41% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability.

An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.