Search results

The purpose of this paper is to present the result of using process mining to model the production planning (PP) process of a manufacturing company that is supported by enterprise resource planning (ERP) systems.

This paper uses event logs obtained from the case company’s ERP database. The steps for this research are planning process mining implementation, extraction and construction of event log, discovering process model with Heuristic Miner and analysis.

Process model obtained from process mining shows how the PP is actually conducted. It shows the loop in materials requirement planning and create plan order process. Furthermore, the occurrences of changing plan order date and production line indicate the schedule instability in the case company. Further analysis of the material management (MM) event log shows the implication of production plan changes on MM. Continuous change in the plan affects material allocation priority and may result in a mismatch between production needs and the materials available.

The study is only conducted in a single and specific case. Therefore, even though the findings provide good insight, the use of solitary case study does not imply a general result applied to other cases. Hence, there is a need to conduct similar studies on various cases so that a more generic conclusion can be drawn.

The result provides insights into how the current company’s policy of adjusting the production plan to accommodate changing demand impacts their operation. It can help the company to consider a better balance between flexibility and efficiency to improve their process.

The paper demonstrates the use of process mining to capture the real progression of PP based on the data stored in the company’s ERP database, which give an insight into how a real company conducts their PP process, the implication of schedule instability on MM and production. The novelty of this research lies in the use of process mining to attest to the schedule nervousness issue at a process level.

The classical definition of PDM focuses on the broad spectrum of distribution activity, from the inbound raw materials; to the finished product flow; and to the end user. The definition is often stated as “all of the activities involved in the flow of goods from the manufacturer to the consumer which include inventory control, transportation, warehousing, order processing, materials management, and purchasing”. But despite the broad view described in the definition, little attention is given to the raw materials flow and to the entire area of Materials Management. Physical Distribution managers tend to disregard the inbound flow and regard it as the responsibility of some other management group in the company, specifically purchasing and/or production. The need for a well co‐ordinated and efficient distribution system demands that the PD manager pay more attention to the inbound material flow. The outcome of the decisions that a PD manager makes depends to a great degree on how well materials management and PDM are co‐ordinated in a firm:

This paper proposes an integrated approach that seeks to jointly optimize project scheduling and material lot sizing decisions for time-constrained project scheduling problems.

A mixed integer linear programming model is devised, which utilizes the splitting of noncritical activities as a mean toward leveling the renewable resources. The developed model minimizes renewable resources leveling costs along with consumable resources related costs, and it is solved using IBM ILOG CPLEX optimization package. A hybrid metaheuristic procedure is also proposed to efficiently solve the model for larger projects with complex networks structure.

The results confirmed the significance of the integrated approach as both the project schedule and the material ordering policy turned out to be different once compared to the sequential approach under same parameter settings. Furthermore, the integrated approach resulted in substantial total costs reduction for low values of the acquiring and releasing costs of the renewable resources. Computational experiments conducted over 240 test instances of various sizes, and complexities illustrate the efficiency of the proposed metaheuristic approach as it yields solutions that are on average 1.14% away from the optimal ones.

This work highlights the necessity of having project managers address project scheduling and materials lot sizing decisions concurrently, rather than sequentially, to better level resources and minimize materials related costs. Significant cost savings were generated through the developed model despite the use of a small-scale example which illustrates the great potential that the integrated approach has in real life projects. For real life projects with complex network topology, practitioners are advised to make use of the developed metaheuristic procedure due to its superior time efficiency as compared to exact solution methods.

The sequential approach, wherein a project schedule is established first followed by allocating the needed resources, is proven to yield a nonoptimized project schedule and materials ordering policy, leading to an increase in the project's total cost. The integrated approach proposed hereafter optimizes both decisions at once ensuring the timely completion of the project at the least possible cost. The proposed metaheuristic approach provides a viable alternative to exact solution methods especially for larger projects.

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.

Considerable effort is needed to design the software and the material‐flow system to meet the needs of manufacturing which is driven by customer demand. Top management initiative and support is required throughout. Here, Prof. Dr. Sankaran describes the concept developed by Siemens in two major projects.

Many manufacturing organizations are switching over to JIT manufacturing systems following the success of Japanese industries. Presents a case study of a simulation modelling approach in the design and analysis of a proposed JIT system for an Australian chemical company, which currently operates on a traditional system. The approach was used to compare two cell designs, and to estimate utilization levels for operators and materials handlers under the new system, and to determine reorder levels for raw materials at the work stations in order to operate the JIT system successfully.

The purpose of this paper is to solve an integration of customer and supplier flexibility problem in a make-to-order (MTO) industry. The flexible strategies, where delivery leadtime and unit price (or raw material cost) can be negotiated, are provided by customers and suppliers. Its effectiveness is illustrated by a practical application.

The present study is a rolling decision-making problem and is solved by a proposed combined mixed integer program (MIP) and simulation approach. A simulation model was developed for evaluating solutions of the MIP and will serve as the virtual factory to provide the initial work-in-process status for a new incoming order evaluation.

The experimental results show that when either customers or suppliers provide flexible strategies to the manufacturer, total profits can be increased. Moreover, when both customers and suppliers provide flexibility strategies to the manufacturer simultaneously, total profits can be significantly increased.

An expanded experiment would be of help in realizing the relationship between the flexibility and profit. Moreover, there are other price-sensitivity functions for both customers and suppliers.

A fishing-net manufacturing company was used for the case study to illustrate the effectiveness and the feasibility of the proposed methodology and its application to industry.

The proposed methodology innovatively solved a practical application. The customer and supplier flexibility was investigated in a MTO production system that has no inventory of raw material. The experimental results are promising.

The dynamic nature and complexity of construction projects make it challenging to ensure that the engineer-to-order (ETO) materials supplied onsite match changing needs. The quick and efficient communication of required changes in material fabrication, delivery and use, due to changes in the design and construction schedules, is needed to address the challenges. This study aims to provide a novel integrated management framework with its embedded informatics to help major stakeholders efficiently absorb agility during communication to deal with required changes and improve workflows.

An integrated management framework is developed that integrates the milestones in look-ahead plans and structured iterative processes for major supply chain stakeholders to quickly disseminate information emanating from changes in design, schedules, production and transportation. A prototype system is devised including the informatics to support the framework, which consists of BIM-RFID functional modules and a central database and uses a client-server architecture. The usefulness of the prototype is illustrated using a construction of part of a fictive but realistic high-rise building.

The integrated management framework with the informatics provides major stakeholders with the ability to coordinate their activities efficiently and stimulate their agility (measured by process time) in planning and controlling material information. Although only a fictive example was used, it is shown that the use of the system is likely to result in a substantial reduction in the time required to deal with required changes when delivering ETO materials onsite (by 18% in the example).

The functionalities of the prototype system can be easily scaled up to coordinate changes in the design and scheduling of other types of materials. More functional developments are needed to show the extent of the possible improvement for entire construction projects. Future work should focus on investigating the possible improvements for other types and sizes of construction projects, and eventually in real-world construction projects.

By fitting the look-ahead plans into structured iterative processes through digital data sharing, stakeholders increased their capability to quickly capture required change information and resolve associated problems. This is particularly useful for the management of ETO supply chain processes, where prefabricated elements such as ductwork, plumbing, and mechanical systems typically have to be modified because of last-minute design and schedule changes.

Unlike traditional information technology (IT) based supply chain management practices, this research is characterized by a process-centered management framework that provides explicit decision points over iterative planning processes for major stakeholders to manage material information. The iterations through digital data sharing allow stakeholders to quickly respond to last-minute changes on site, which fundamentally achieves workflow agility in the construction supply chain context.

To develop a systematic procedure and a computerized tool for optimizing the delivery and inventory of materials, as part of a comprehensive material management system in construction projects.

A newly devised approach that employs genetic algorithms (GAs) for the optimization of material delivery schedules and their associated inventory control is presented. The approach is based on the project material requirement plans, and employs an objective function that minimizes the total costs associated with material deliveries. Furthermore, the computer system developed is used to examine and validate the adopted approach.

GA proved to be a satisfactory approach for optimizing material delivery schedules and its associated inventory levels. The selected case study particularly showed the system to produce material delivery plans that have reduced costs compared with their actual counterparts. Also, the computer processing time for developing the optimized plans was rather minimal, which promote its practical use.

The paper addresses one part of the comprehensive material management system; that is the optimization of the material delivery schedules and inventory control. Other future publications by the same authors will address the issues of probabilistic lead time calculations and development of material ordering schedules.

The paper partially fulfills a long‐sought research need for developing comprehensive material management systems specifically tailored to construction projects. The system takes into account several parameters that are not typically incorporated in the economic order quantity models for material management. Furthermore, practicality of the introduced system is augmented by the fact that it is interlinked with one of the most commonly used scheduling software.

Changes frequently made to material delivery schedules (MDSs) accumulate upstream in the supply chain (SC), causing a bullwhip effect. This article seeks to elucidate how dynamic complexity generates MDS instability at OEMs in the automotive industry.

An exploratory multiple-case study methodology involved in-depth semistructured interviews with informants at three automotive original equipment manufacturers (OEMs).

Dynamic complexity destabilizes MDSs primarily via internal horizontal interactions between product and process complexities and demand and SC complexities. A network of complexity interactions causes and moderates such instability through complexity absorption and generation and complexity importation and exportation.

The multiple-case study contributes to empirical knowledge about the dynamics of MDS instability. Deductive research to validate the identified relationships remains for Future research.

In revealing antecedents of complexity’s effect on MDS instability, the findings imply the need to develop strategies, programs, and policies dedicated to improving capacity scalability, supplier flexibility, and the flexibility of material order fulfillment.

Building on complexity literature, the authors operationalize complexity transfer and develop a framework for analyzing dynamic complexity in SCs, focusing on complexity interactions. The identification and categorization of interactions provide a granular view of the dynamic complexity that generates MDS instability. The identified and proposed importance of readiness of the SC to absorb complexity challenges the literature focus on external factors for explaining complexity outcomes. The results can be used to operationalize such dynamic interactions by introducing new variables and networks of relationships. Moreover, the work showcases how a complexity perspective could be used to discern the root causes of a complex phenomenon driven by non-linear relationships.