Robustness assessment in production systems

2021 ◽  
Vol 32 (4) ◽  
pp. 932-951
Author(s):  
Christian Stockmann ◽  
Herwig Winkler ◽  
Martin Kunath

PurposeThe concept of robustness in manufacturing is not easy to capture and even harder to quantify. This paper elaborates an approach to assess robustness in production systems from a holistic input-throughput-output perspective using a pragmatic robustness indicator.Design/methodology/approachFirst, in order to have a precise understanding of what needs to be measured, a concept of robustness in production systems is defined based on a literature overview. Three different aspects are considered to be essential to comprehensively describe robustness in production: the deviations of input resources, of performance and of output. These aspects are translated into an aggregated indicator based on developments of production costs, order delays and output volumes. The indicator-based assessment approach is eventually applied to a flow-shop scheduling case study in the chipboard industry.FindingsThe study shows that an assessment of robustness should not solely focus on a single aspect of a production system. Instead, a holistic view is required addressing the tradeoffs that robustness must balance, such as the one between the realized performance, the corresponding resource requirements and the resulting output. Furthermore, the study emphasizes that robustness can be interpreted as a superior system capability that builds upon flexibility, agility, resilience and resistance.Research limitations/implicationsFirst, the paper is a call to further test and validate the proposed approach in industry case studies. Second, the paper suggests a modified understanding of robustness in production systems in which not only the deviation of one single variable is of interest but also the behavior of the whole system.Practical implicationsThe approach allows practitioners to pragmatically evaluate a production system’s robustness level while quickly identifying drivers, barriers and tradeoffs.Originality/valueCompared to existing assessment approaches the proposed methodology is one of the first that evaluates robustness in production systems from a holistic input-throughput-output perspective highlighting the different tradeoffs that have to be balanced. It is based upon a comprehensive concept of robustness which also links robustness to adjacent capabilities that were otherwise only treated separately.

2019 ◽  
Vol 14 (1) ◽  
pp. 232-259 ◽  
Author(s):  
Ata Allah Taleizadeh ◽  
Mahshid Yadegari ◽  
Shib Sankar Sana

Purpose The purpose of this study is to formulate two multi-product single-machine economic production quantity (EPQ) models by considering imperfect products. Two policies are assumed to deal with imperfect products: selling them at discount and applying a reworking process. Design/methodology/approach A screening process is used to identify imperfect items during and after production. Selling the imperfect items at a discount is examined in the first model and the reworking policy in the second model. In both models, demand during the production process is satisfied only by perfect items. Data collected from a case company are used to illustrate the performance of the two models. Moreover, a sensitivity analysis is carried out by varying the most important parameters of the models. Findings The case study in this research is used to demonstrate the applicability of the proposed models, i.e. the EPQ model with salvaging and reworking imperfect items. The models are applied to a high-tech un-plasticized polyvinyl chloride (UPVC) doors and windows manufacturer that produces different types of doors and windows. ROGAWIN Co. is a privately owned company that started in 2001 with fully automatic production lines. Finally, the results of applying the different ways of handling the imperfect items are discussed, along with managerial insights. Originality/value In real-world production systems, manufacturing imperfect products is unavoidable. That is why, it is important to make a proper decision about imperfect products to reduce overall production costs. Recently, applying a reworking strategy has gained the most interest when it comes to handling this problem. The principal idea of this research is to maximize the total profit of manufacturing systems by optimizing the period length under some capacity constraints. The proposed models were applied to a company of manufacturing UPVC doors and windows.


2019 ◽  
Vol 39 (5) ◽  
pp. 944-962 ◽  
Author(s):  
Sahar Tadayonirad ◽  
Hany Seidgar ◽  
Hamed Fazlollahtabar ◽  
Rasoul Shafaei

Purpose In real manufacturing systems, schedules are often disrupted with uncertainty factors such as random machine breakdown, random process time, random job arrivals or job cancellations. This paper aims to investigate robust scheduling for a two-stage assembly flow shop scheduling with random machine breakdowns and considers two objectives makespan and robustness simultaneously. Design/methodology/approach Owing to its structural and algorithmic complexity, the authors proposed imperialist competitive algorithm (ICA), genetic algorithm (GA) and hybridized with simulation techniques for handling these complexities. For better efficiency of the proposed algorithms, the authors used artificial neural network (ANN) to predict the parameters of the proposed algorithms in uncertain condition. Also Taguchi method is applied for analyzing the effect of the parameters of the problem on each other and quality of solutions. Findings Finally, experimental study and analysis of variance (ANOVA) is done to investigate the effect of different proposed measures on the performance of the obtained results. ANOVA's results indicate the job and weight of makespan factors have a significant impact on the robustness of the proposed meta-heuristics algorithms. Also, it is obvious that the most effective parameter on the robustness for GA and ICA is job. Originality/value Robustness is calculated by the expected value of the relative difference between the deterministic and actual makespan.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yuquan Wang ◽  
Naiming Xie

Purposepurpose of this paper is providing a solution for flexible flow shop scheduling problem with uncertain processing time in aeronautical composite lay-up workshop.Design/methodology/approachA flexible flow scheduling model and algorithm with interval grey processing time is established. First, according to actual needs of composite laminate shop scheduling process, interval grey number is used to represent uncertain processing time, and interval grey processing time measurement method, grey number calculation and comparison rules, grey Gantt chart, and other methods are further applied. Then a flexible flow shop scheduling model with interval grey processing time (G-FFSP) is established, and an artificial bee colony algorithm based on an adaptive neighbourhood search strategy is designed to solve the model. Finally, six examples are generated for simulation scheduling, and the efficiency and performance of the model and algorithm are evaluated by comparing the results.FindingsResults show that flexible flow shop scheduling model and algorithm with interval grey processing time can provide an optimal solution for composite lay-up shop scheduling problems and other similar flow shop scheduling problems.Social implicationsUncertain processing time is common in flexible workshop manufacturing, and manual scheduling greatly restricts the production efficiency of workshop. In this paper, combined with grey system theory, an intelligent algorithm is used to solve flexible flow shop scheduling problem to promote intelligent and efficient production of enterprises.Originality/valueThis paper applies and perfects interval grey processing time measurement method, grey number calculation and comparison rules, grey Gantt chart and other methods. A flexible flow shop scheduling model with interval grey processing time is established, and an artificial bee colony algorithm with an adaptive domain search strategy is designed. It provides a comprehensive solution for flexible flow shop scheduling with uncertain processing time.


SINERGI ◽  
2021 ◽  
Vol 25 (2) ◽  
pp. 111
Author(s):  
Masrikhan Masrikhan ◽  
Dwi Agustina Kurniawati

In the manufacturing industry, the most widely used equipment is equipment that uses electricity. Electricity cost is one of the highest operational production costs after labor cost. So, it is very important to save and optimize the use of electrical equipment. One of the manufacturing industries is Taru Martani, Ltd. This research aims to minimize the energy cost by proposing three hybrid algorithms, namely Palmer-NEH, Gupta-NEH, and Dannenbring-NEH methods. Some scheduling evaluation is done using the Efficiency Index (EI) and Relative Error (RE) parameters. It is concluded that the Palmer-NEH and Gupta-NEH methods are the best methods with the lowest energy cost compared with company's actual method and the Dannenbring-NEH method. Based on the Palmer-NEH and Gupta-NEH methods, both methods can save the makespan up to 399.13 minutes or 6.65 hours compared with the company's actual method. With these methods, the company is also able to save the production cost by Rp. 818,043.00.


2018 ◽  
Vol 31 (6) ◽  
pp. 925-936 ◽  
Author(s):  
Orhan Engin ◽  
Batuhan Engin

Purpose Hybrid flow shop with multiprocessor task (HFSMT) has received considerable attention in recent years. The purpose of this paper is to consider an HFSMT scheduling under the environment of a common time window. The window size and location are considered to be given parameters. The research deals with the criterion of total penalty cost minimization incurred by earliness and tardiness of jobs. In this research, a new memetic algorithm in which a global search algorithm is accompanied with the local search mechanism is developed to solve the HFSMT with jobs having a common time window. The operating parameters of memetic algorithm have an important role on the quality of solution. In this paper, a full factorial experimental design is used to determining the best parameters of memetic algorithm for each problem type. Memetic algorithm is tested using HFSMT problems. Design/methodology/approach First, hybrid flow shop scheduling system and hybrid flow shop scheduling with multiprocessor task are defined. The applications of the hybrid flow shop system are explained. Also the background of hybrid flow shop with multiprocessor is given in the introduction. The features of the proposed memetic algorithm are described in Section 2. The experiment results are presented in Section 3. Findings Computational experiments show that the proposed new memetic algorithm is an effective and efficient approach for solving the HFSMT under the environment of a common time window. Originality/value There is only one study about HFSMT scheduling with time window. This is the first study which added the windows to the jobs in HFSMT problems.


Author(s):  
Toni Luomaranta ◽  
Miia Martinsuo

Purpose Additive manufacturing (AM) involves the renewal of production systems and also has implications for firms’ supply chains. Innovations related to AM supply chains are, so far, insufficiently understood, but their success will require firms’ awareness of their systemic nature and their firm-specific implications. The purpose of this paper is to explore the supply chain innovations dealing with AM in business-to-business supply chains. Design/methodology/approach An exploratory qualitative research design is used. Interviews were conducted in 20 firms, workshops were organized to map AM-related processes and activities, and supply chain innovations were analyzed. Findings This study reveals practical changes in supply chains and requirements for AM-related supply chain innovations. While earlier research has centered on technology or firm-specific AM implementations, this study shows that fully leveraging AM will require innovations at the level of the supply chain, including innovations in business processes, technology and structure, as well as supportive changes in the business environment. These innovations occur in different parts of the AM supply chain and are emphasized differently within different firm types. Research limitations/implications This research was conducted in one country in the context of the machine building and process industry with a limited data set, which limits the generalizability of the results. The results offer an analytical framework and identify new research avenues for exploring the innovations in partial or complete AM supply chains. Practical implications The results offer a framework to assess the current state and future needs in AM-related supply chain innovations. Practical ideas are proposed to enhance AM adoption throughout firms’ supply chains. These results are important to managers because they can help them position their firms and guide the activities and collaborations with other firms in the AM supply chain. Originality/value This study draws attention to the supply chain innovations required when firms adopt AM in their processes. The generic supply chain innovation framework is enhanced by adding the business context as a necessary component. Implementation of AM is shown to depend on the context both at the level of the supply chain and the firm’s unique role in the supply chain. The holistic view taken reveals that successful AM technology adoption requires broad involvement from different firms across the supply chain.


Author(s):  
Fatima Ghedjati ◽  
Safa Khalouli

In this chapter the authors address a hybrid flow shop scheduling problem considering the minimization of the makespan in addition to the sum of earliness and tardiness penalties. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, to deal with this problem, the authors propose a method which consists on the one hand, on using a meta-heuristic based on ant colony optimization algorithm to generate feasible solutions and, on the other hand, on using an aggregation multi-criteria method based on fuzzy logic to assist the decision-maker to express his preferences according to the considered objective functions. The aggregation method uses the Choquet integral. This latter allows to take into account the interactions between the different criteria. Experiments based on randomly generated instances were conducted to test the effectiveness of the approach.


2018 ◽  
Vol 120 (8) ◽  
pp. 1876-1887 ◽  
Author(s):  
Xiomara Fernanda Quiñones Ruiz ◽  
Hanna Forster ◽  
Marianne Penker ◽  
Giovanni Belletti ◽  
Andrea Marescotti ◽  
...  

Purpose The protection of Geographical Indications (GIs) supports producers to define common quality standards while highlighting the geographical origin of food products with specific qualities. Adaptations of quality standards are driven by international competition, new production technologies or environmental change. The purpose of this paper is to analyse the modifications affecting European Union (EU) Protected Designation of Origin-Protected Geographical Indication. It specifically compares the share of amendments in diverse product class, years and countries, illustrates specific cases and identifies the factors explaining the probability to amend product specifications. Design/methodology/approach Official documents of the DOOR Database provide the material for an analysis of changes in product specifications. They also supply the data for four illustrative cheese cases and a logistic regression of all EU amendments. Findings Amendments of GI product specifications are very frequent: 17 per cent of all 1,276 EU GIs had at least one amendment. This happens in particular for processed products (42 per cent more often than for unprocessed ones) and specific countries (GIs in Italy are six times, Spain five times and France four times more likely to have an amendment compared to GIs from other EU countries). As illustrated by contrasting cheese amendments, the diverse modifications in the product specifications range from more flexibility and innovation on the one hand to stricter rules for strengthening the product’s identity on the other hand. Originality/value For EU and national authorities, GI producers and scholars, this first systematic EU-wide analysis of amendments demonstrates that protected food GIs have to be conceptualised as evolving institutions and not as statically protected food production systems.


Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 799
Author(s):  
Basit Farooq ◽  
Jinsong Bao ◽  
Qingwen Ma

Pointed at a problem that leads to the high complexity of the production management tasks in the multi-stage spinning industry, mixed flow batch production is often the case in response to a customer’s personalized demands. Manual handling cans have a large number of tasks, and there is a long turnover period in their semi-finished products. A novel heuristic research was conducted that considered mixed-flow shop scheduling problems with automated guided vehicle (AGV) distribution and path planning to prevent conflict and deadlock by optimizing distribution efficiency and improving the automation degree of can distribution in a draw-out workshop. In this paper, a cross-region shared resource pool and an inter-regional independent resource pool, two AGV predictive scheduling strategies are established for the ring-spinning combing process. Besides completion time, AGV utilization rate and unit AGV time also analyzed with the bottleneck process of the production line. The results of the optimal computational experiment prove that a draw frame equipped with multi-AGV and coordinated scheduling optimization will significantly improve the efficiency of can distribution. Flow-shop predictive modeling for multi-AGV resources is scarce in the literature, even though this modeling also produces, for each AGV, a control mode and, if essential, a preventive maintenance plan.


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