A survey of simulation modeling techniques in production planning and control (PPC)

The manufacturing sector as a whole has undergone remarkable changes in terms of scale, complexity and technology over the past decades and this applies across most modern high-technology manufacturing such as electronics, semiconductor, aerospace and automotive industries. In order to remain competitive, manufacturers have to produce high-quality products at low cost, and at the same time retain sufficient flexibility and to meet rapidly changing customer demands. Production planning and control (PPC) is a key role which enables the manufacturer to gain visibility and control over all aspects of manufacturing activities. PPC in itself forms a subject of study, within which simulation techniques have proven themselves to be one of the most practical methodologies available to investigate and evaluate manufacturing issues. In this review paper, we focus on state-of-the art applications of simulation techniques in PPC to demonstrate their applicability to modern manufacturing issues. The review reports on academic publications on simulation applications in manufacturing from 2002 to 2014, incorporating surveys of peer-reviewed literature. The review covers three types of simulation techniques (system dynamic, discrete event simulation and agent-based simulation) and eight PPC issues (facility resource planning, capacity planning, job planning, process planning, scheduling, inventory management, production and process design, purchase and supply management). Literature survey is analysed on the basis of simulation application to PPC problems which can give a guideline for simulation technique selection and also can help for simulation modelling in PPC problemsWould you consider changing the term “modeling” to “modelling” in the title. Please check, and correct if necessary.     

Neural networks in production planning and control

The purpose of this paper is to present a selection of the most significant ANN (artificial neural network) applications used to solve PPC (production planning and control) problems. Therefore, the paper itself is a reasoned classification rather than a simple survey. The PPC domain is divided into various areas, and for each area one or more examples of ANNs are discussed, together with the benefits and drawbacks of their application to that particular area. Finally, two case studies developed by the authors are reported and discussed to analyse the main implementation problems to be considered when using ANNs.     

Multi-site aggregate production planning with multiple objectives: A goal programming approach

This paper addresses the problem of aggregate production planning (APP) for a multinational lingerie company in Hong Kong. The multi-site production planning problem considers the production loading plans among manufacturing factories subject to certain restrictions, such as production import/export quotas imposed by regulatory requirements of different nations, the use of manufacturing factories/locations with regard to customers' preferences, as well as production capacity, workforce level, storage space and resource conditions of the factories. In this paper, a multi-objective model is developed to solve the production planning problems, in which the profit is maximized but production penalties resulting from going over/under quotas and the change in workforce level are minimized. To enhance the practical implications of the proposed model, different managerial production loading plans are evaluated according to changes in future policy and situation. Numerical results demonstrate the robustness and effectiveness of the developed model.     

Selection and implementation of a PPC system

There are many computer-aided production planning and control (PPC) systems available on the market which can provide a solution to the complex task of production planning and control. However, the question remains, how can a company find an optimal system from the vast amount of available systems? This article proposes that a company, having decided to buy one of the available systems, starts a project for selection and implementation of the PPC system.     

Computational complexity of algorithms for MRP and JIT production planning problems in enterprise resource planning systems

An enterprise resource planning system (ERP) is the information backbone of many manufacturing companies. At the core of ERP is a conventional material requirements planning (MRP) production planning system or a variation of MRP when just-in-time (JIT) principles are used in manufacturing. MRP and JIT both organize production planning into a hierarchy of long-, medium- and short-range problems. In all there are eight different problems. Some are common to MRP and JIT, others are specialized for a particular system. This paper analyses the computational requirements of these problems. This is important for ERP because it plans for large numbers of products (e.g. 50 000 products at 3M Company and 44 000 products at States Industries in Oregon) at large numbers of locations (e.g. 82 locations in 21 countries for Visteon Automotive Systems of Michigan and 19 locations at Boeing). We show that adequate algorithms exist for some problems, but better algorithms are needed for other problems if ERP is to provide useful production plans.     

Production planning and control in automated manufacturing systems

Automated manufacturing systems (AMSs) have the potential for providing a high level of manufacturing performance. Owing to the high cost of capital investment, a high utilization level of AMSs with the help of suitable production planning and control (PPC) is feature of AMSs. Realizing the potential of PPC in AMSs, an attempt has been made to review the available techniques/methods for solving the problems of production planning, control and scheduling in AMSs. The need for further research on PPC of AMSs is brought to the fore along with future research directions.     

The myth of aggregate planning

Abstract

Abstract. An empirical study explores the business environment, the nature of manufacturing, and the planning cycle, using a sample of enterprises with seasonally-biased sales profiles for their products. This enables both the principles and the practicalities of aggregate planning to stand comparison with the observed rubric of manufacturing management. The conclusion is that neither is germane to industry, and that, in general, practitioners develop an effective (broad) manufacturing strategy with an appropriate resources-acquisition programme. The master production schedule then strikes an acceptable balance between productivity, flexibility, and financial risk.     

Experimental earliness/tardiness production planning with the due window system

In order to use the philosophy of JIT to improve the production planning method of MRP-II, we propose the experimental software system of the earliness/tardiness produc tion planning problem with due window. By means of the approaches and model reported in this paper, the optimal production planning can be achieved. The recommended model extends the problem of due window from the shop scheduling level into the aggregated planning level of mass manufacturing systems. Simulation results have demonstrated that the experimental software is a useful tool for the production management of repetitive manufacturing enterprises.     

Genetic algorithm to production planning and scheduling problems for manufacturing systems

Fundamental and extended multi-objective (MO) models are designed to address earliness/tardiness production scheduling planning (ETPSP) problems with multi-process capacity balance, multi-product production and lot-size consideration. A canonical genetic algorithm (GA) approach and a prospective multi-objective GA (MOGA) approach are proposed as solutions for different practical problems. Simulation results as well as comparisons with other techniques demonstrate the effectiveness of the MOGA approach, which is a noted improvement to any of the existing techniques, and also in practice provides a new trend of integrating manufacturing resource planning (MRPII) with just-in-time (JIT) in the production planning procedure.     

Integration of CAD/CAM and production control in sheet metal manufacturing — an application area of operations research

Abstract

This paper describes a process planning system for sheet metal parts. This system has capabilities to deliver process planning data just in time. The change of tools, processes and even machines for manufacturing of the parts is possible at the shop door after design has been finished.

The sequence of the production planning steps carried out can be changed. In this way the system can be adapted to the requirements of different sheet metal manufacturing companies.

More detailed information is given about the methods used for nesting of the workpieces on the sheets to be produced.     

Flexible reasoning using sensible agent-based systems: A case study in job flow scheduling

Planning and control systems for highly dynamic and uncertain manufacturing environments require adaptive flexibility and decision-making capabilities. Modern distributed manufacturing systems assess the utility of planning and executing solutions for both system goals (e.g. minimize manufacturing production time for all parts or minimize WIP) and local goals (e.g. expedite part A production schedule or maximize machine X utilization). Sensible Agents have the ability to alter their autonomy levels to choose among a set of decision models in order to handle the differences between local and system goals. In this paper, Sensible Agents are applied to a production planning and control problem in the context of job shop scheduling and decision model theory. Sensible Agents provide for trade-off reasoning mechanisms among system and local utilities that are flexible and responsive to an agent's abilities, situational context and position in the organizational structure of the system.     

A general approach to disassembly planning and control

Closing product and material cycles have emerged as a paradigm for industry in the 21st century, and are directed towards an economical and responsible use of our limited resources. Disassembly plays a key role in recycling. It enables the recovery of functioning components for re-use of pure materials for re-utilization and the separation of harmful substances. Major challenges are presented by the enormous variety of products to be disassembled, by uncertainty as to quantity and by their unknown properties. An appropriate planning and control of disassembly processes is essential for an economic disassembly. Based on an investigation of the suitability of common production planning and control (PPC) methods for disassembly, a specific disassembly planning and control concept (DPC) is outlined.     

Period batch control: Classic,not outdated

Period Batch Control was developed and first applied during the Second World War. The historic roots are discussed and the principles of this classic production planning approach explained, PBC compared to other production control concepts, and it is demonstrated that it may still be fruitfully applied, especially in combination with cellular manufacturing. It is therefore considered as a classic, but not outdated production planning concept.     

The implementation of digital technologies for operations management: a case study for manufacturing apps

Abstract

Manufacturing applications address business to business (B2B) with highly customised applications developed for specific requirements, offering highly specialised solution-oriented and service-based software components, systems, and digital tools that aim at a fast and accurate decision-making support system. The purpose of this paper is to describe the implementation of digital technologies for operations management using manufacturing or engineering apps (eApps), for product design and manufacturing processes. In particular, starting from the specific needs of two companies from mature European industries as automotive and food, this work depicts how this kind of solutions can support companies and improve their operations. In particular, related benefits and challenges faced for the full implementation of the developed tools are highlighted. Moreover a business model to exploit the manufacturing apps is also proposed. The business model proposed for the exploitation of the eApps supports the commercialisation of all the revenue streams offered by this rapidly growing sector taking into account the specific needs of the concerned stakeholders through a diversified value proposition.     

Production planning and inventory control in a company manufacturing PC parts: A case study

In this paper, we present a case study on the production planning and inventory system in a company manufacturing personal computer (PC) parts. In the case study, the targets are specified for developing a system for production planning and inventory control. The current state of the company is analysed for clarifying the points necessary to achieve the targets. Also, a system based on the analysis is proposed and its effects are estimated.     

Aggregate production planning with workforce transferring plan for multiple product types

This paper presents the aggregate production planning for multiple product types where the worker resource can be transferred among the production lines. A mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A real situation of a manufacturing company was selected as a case study. The actual data was used to test and validate the proposed model. The optimal aggregate production plan provides the information on managing the available production capacity together with the useful workforce transferring plan. The obtained solutions were compared to those of another approach where the workers cannot be transferred among the production lines. The total cost is significantly reduced when the workers are allowed to transfer among the production lines.     

A finite capacity material requirements planning system

In a discrete parts manufacturing environment, material requirement planning (MRP) is carried out without considering the manufacturing resource capacity. As a result, during implementation, adjustments in planned orders may become necessary. This paper presents a finite capacity material requirements planning algorithm (FCMRP) to obtain capacity-based production plans. These plans need no costly adjustments to satisfy the capacity constraints. Performance of the FCMRP system, when studied through a set of test examples, has been found to be superior to the existing MRP system.     

Production planning and control tools

There are numerous tools available to be used for production planning and control purposes. The number of tools is ever increasing, and so are the levels of sophistication as well as complexity. For the specific manufacturing firm, the task of selecting the most appropriate set of tools is not trivial. However, in recent years, the understanding of the relationship between tools and manufacturing environments for which they are suitable has increased. The purpose of this paper is to provide an overview of production planning and control tools available today, as well as new trends, issues and ideas.     

The effect of knowledge collaboration on business model reconfiguration

This study examines whether and to what extent the presence and intensity of knowledge collaboration across different partners affects business model reconfiguration (BMR). We build on the business model (BM) literature and operationalize BMR by introducing the presence and intensity of collaboration and firm size effects as main explanatory factors in affecting the propensity of incremental and radical BMR. We analyze a large sample of UK firms during 2002–2014 to capture the effect of knowledge collaboration and firm size on BMR. Positively incremental forms of BMR will be influenced by the presence and intensity of knowledge collaboration, while radical forms of BMR are affected by the intensity of collaboration with customers and the collaboration with suppliers by large firms. Furthermore, firms of different sizes do not equally benefit from knowledge collaboration with suppliers for both incremental and radical BMR, while they do equally benefit from collaboration with other partner types.     

An icon-based data image construction method for production data visualization

Visualization takes advantage of human's rapid and flexible pattern recognition capacity to provide a powerful information-processing environment. It is especially suitable for identifying patterns that are difficult, or impossible, to be defined by a mathematical or computer model. This paper presents an icon-based method for constructing images to visualize the abstract, multidimensional production data stored in tables. The method employs a simple, topology-preserving mapping to convert numbers in a table to icons. This mapping strategy not only makes the meaning of the resulted data image easy to understand, but also makes the maximum number of dimensions and data items that could be displayed be virtually unlimited. Visual patterns in the data image are formed by adjacent icons that have similar grey scales. The area sampling techniques could be applied to reduce the size of the data image while still retaining its visual patterns. The proposed visualization method has been applied to several production planning and control activities, including analysing WIP patterns, production indices, and the machine idle cost performance of production plans. These industrial case studies demonstrate that the ability to quickly and easily examine large amount of manufacturing data through visualization is critical for manufacturing companies to understand their performance, discover possible problems and take necessary actions so that they could remain competitive in the market.