Impact of inventory storage and retrieval schemes on productivity

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.Includes bibliographical references.The operational management of high volume, multi-line distribution warehouses is a monumental undertaking, which only a handful of companies in the world have chosen to tackle. Amazon.com is amongst the few, and has further differentiated itself because of its direct to customer method of distribution and complex order mixes. There is no other retailer that carries and directly delivers as many different products (over 4 million different unique items) in as wide range of product categories (from music to cosmetics to electronics to garden hoses) in as high of volume as Amazon.com. The nature of Amazon's retail model and its organic growth over the past decade has made its fulfillment centers a complex beast to decipher. Decisions on the fulfillment center floor are composed of intricate balances between demand constraints, equipment bottlenecks, storage limitations and labor costs, making the true cost associated with each variable dependent on every other variable. The goal of this thesis is to document a practical exploration of inventory storage and retrieval schemes and its relationships to productivity (and subsequently cost), as well as identify implementable changes that yields higher throughput, lower lead time for order fulfillment, and ultimately dollar savings. Of particular interest are operationally transparent process changes, which improve processes in a manner that minimize impact on the fulfillment center floor. This concept will be the central theme of all recommendations resulting from this thesis.by Charlene (Charlie) A. Lieu.S.M.M.B.A

Behavior of bucket brigade in an order-picking system under the effect of fatigue

Il lavoro considera l’effetto della fatica sugli operatori in un bucket-brigade in un sistema di order-picking. Lo scopo dell’ elaborato è quello di studiare il comportamento di tutti i possibili tipi di bucket brigade e decidere quali sono i più performanti. I risultati sono stati ottenuti sia numericamente con MATLAB che analiticamente. Oltre a presentare i risultati ottenuti, sono fornite anche delle istruzioni che il manager deve seguire per massimizzare la performance del sistema

New Solution Approaches for Scheduling Problems in Production and Logistics

The current cumulative PhD thesis consists of six papers published in/submitted to scientific journals. The focus of the thesis is to develop new solution approaches for scheduling problems encountering in manufacturing as well as in logistics. The thesis is divided into two parts: “ma-chine scheduling in production” and “scheduling problems in logistics” each of them consisting three papers. To have most comprehensive overview of the topic of machine scheduling, the first part of the thesis starts with two systematic review papers, which were conducted on tertiary level (i.e., re-viewing literature reviews). Both of these papers analyze a sample of around 130 literature re-views on machine scheduling problems. The first paper use a subjective quantitative approach to evaluate the sample, while the second papers uses content analysis which is an objective quanti-tative approach to extract meaningful information from massive data. Based on the analysis, main attributes of scheduling problems in production are identified and are classified into sever-al categories. Although the focus of both these papers are set to review scheduling problems in manufacturing, the results are not restricted to machine scheduling problem and the results can be extended to the second part of the thesis. General drawbacks of literature reviews are identi-fied and several suggestions for future researches are also provided in both papers. The third paper in the first part of the thesis presents the results of 105 new heuristic algorithms developed to minimize total flow time of a set of jobs in a flowshop manufacturing environ-ment. The computational experiments confirm that the best heuristic proposed in this paper im-proves the average error of best existing algorithm by around 25 percent. The first paper in second part is focused on minimizing number of electric tow-trains responsi-ble to deliver spare parts from warehouse to the production lines. Together with minimizing number of these electric vehicles the paper is also focused to maximize the work load balance among the drivers of the vehicles. For this problem, after analyzing the complexity of the prob-lem, an opening heuristic, a mixed integer linear programing (MILP) model and a taboo-search neighborhood search approach are proposed. Several managerial insights, such as the effect of battery capacity on the number of required vehicles, are also discussed. The second paper of the second part addresses the problem of preparing unit loaded devices (ULDs) at air cargos to be loaded latter on in planes. The objective of this problem is to mini-mize number of workers required in a way that all existing flight departure times are met and number of available places for building ULDs is not violated. For this problem, first, a MILP model is proposed and then it is boosted with a couple of heuristics which enabled the model to find near optimum solutions in a matter of 10 seconds. The paper also investigates the inherent tradeoff between labor and space utilization as well as the uncertainty about the volume of cargo to be processed. The last paper of the second part proposes an integrated model to improve both ergonomic and economic performance of manual order picking process by rotating pallets in the warehouse. For the problem under consideration in this paper, we first present and MILP model and then pro-pose a neighborhood search based on simulated annealing. The results of numerical experiment indicate that selectively rotating pallets may reduce both order picking time as well as the load on order picker, which leads to a quicker and less risky order picking process

New solution approaches for optimization problems with combinatorial aspects in logistics management

This dissertation comprises five papers, which have been published in scientific journals between 2019 and 2022. The papers consider logistic optimization problems from three different subjects with a focus on intra-logistics. All considered optimization problems have strong combinatorial aspects. To solve the considered problems, various solution approaches including different decomposition techniques are employed. Paper 1 investigates the optimization of the layout and storage assignment in warehouses with U-shaped order picking zones. The paper considers two objectives, namely minimizing the order picker's walking distance and physical strain during order picking. To solve the problem, a semantic decomposition approach is proposed, which solves the problem in polynomial time. In a computational study, both considered objectives are found to be mostly complementary. Moreover, suggestions for advantageous layout designs and storage assignments are derived. Paper 2 considers the problem of how to stow bins on tow trains in order to minimize the handling personnel's physical strain for loading and unloading. The problem is shown to be NP-hard and decomposed semantically. Utilising the decomposition, the problem is solved exactly with dynamic programming and heuristically with a greedy randomized adaptive search procedure. A consecutive computational study shows that both procedures perform well. Beyond that, it investigates the influence of the tow train wagons' design on the considered objective. Paper 3 is concerned with the problem of scheduling jobs with time windows on unrelated parallel machines, which is a NP-hard optimization problem that has applications, i.a., in berth allocation and truck dock scheduling. The paper presents an exact logic-based Benders decomposition procedure and a heuristic solution approach based on a set partitioning formulation of the problem. Moreover, three distinct objectives, namely minimizing the makespan, the maximum flow time, and the maximum lateness are considered. Both procedures exhibit good performances in the concluding computational study. Paper 4 addresses the problem of order picker routing in a U-shaped order picking zone with the objective of minimizing the covered walking distance. The problem is proven to be NP-hard. An exact logic-based Benders decomposition procedure as well as a heuristic dynamic programming approach are developed and shown to perform well in computational tests. Beyond that, the paper discusses different storage assignment policies and compares them in a numeric study. Paper 5 studies scheduling electrically powered tow trains in in-plant production logistics. The problem is regarded as an Electric Vehicle Scheduling Problem, where tow trains must be assigned to timetabled service trips. Since the tow trains' range is limited, charging breaks need to be scheduled in-between trips, which require detours and time. The objective consists in minimizing the required fleet size. The problem is shown to be NP-hard. To solve the problem, Paper 5 proposes a branch-and-check approach that is applicable for various charging technologies, including battery swapping and plug-in charging with nonlinear charge increase. In a computational study, the approach's practical applicability is demonstrated. Moreover, influences of the batteries' maximum capacity and employed charging technology are investigated

Designing a cellular-based fully automated case picking system

Order picking (OP) is the most expensive and labor-intensive activity in warehouses. Some authors argue that OP might be responsible for up to 55% of the operating costs in a warehouse. This might be more important for companies that handle large volumes of fast-moving commodities. Full-case picking processes and mixed pallet building are expensive and complex activities. Companies are looking for technologies to improve their efficiency and to reduce the operating costs of non-value added activities in their warehouses and distribution centers (DCs). Nowadays, the designers of order picking systems face great challenges due to increasing labor costs, less space and more frequent small orders with short delivery times. Consequently, there are constant research efforts devoted to finding new innovative full-case picking solutions that reduce operating costs, generate higher productivity, optimize space utilization and enhance customer service levels. This dissertation presents a new fully automated case picking system (ACPS) called the Automated Cellular Case Picking System (ACCPS). The new system is characterized by the full and permanent accessibility of all stock keeping units (SKUs) in the system, which permits a strategic higher picking rate. This new system could be applied to different levels of automation within warehouses and DCs, and it is suitable for a wide range of warehouse automation requirements. The proposed design consists of storage cells with the same design and operating principle as the vertical indexing case elevator, installed on one conveyor to form a storage line. Several storage lines are connected by a distributing conveyor from the inlet side and by a collecting conveyor from the outlet side, to form an ACCPS use-case model. The concept of this new system is based on the A-Farm concept, in order to create a new innovative dispensing and buffering system for cases. ACCPS is a new concept for a full-case picking system that aims to provide better solutions for warehouses and DCs that deal with a high volume and low variety of products, which are handled in plastic crates or trays. ACCPS would be an efficient solution for many types of commodities such as (food, beverage, grocery, dairy, flowers, sausage, bakery and others). Optimizing picking processes, minimizing operating cost, and increasing efficiency are the most important aims of the new proposed design. This research investigates the layout, design, structure, costs, operating principles, cycle time, and throughput of the new system. A simple logic process was applied to create a mathematical model in order to calculate the expected average time of the order picking and the throughput of this new ACPS. A simulation model has been developed to aid in measuring the effectiveness of the ACCPS proposed design under real operating conditions. Two case studies have been used to evaluate the performance of the new system. Based on the real-time data of these two cases, many simulation scenarios were studied and analyzed in order to solve the storage assignment problem and to determine the best order picking strategy. Many optimization scenarios were simulated and analyzed in order to determine the optimum scenario. In order to evaluate the ACCPS performance, a comparison was made between ACCPS and an alternative system with the same features. The alternative system, which is the most competitive system compared to the ACCPS, is the Gantry Robot System (GRS). The costs, throughput, and required areas were chosen as the main criteria for comparison between the two systems. The comparison confirmed the benefits of the ACCPS in decreasing the operating costs, required area, energy consumption, and the picking time. ACCPS also increased the space utilization rate and the throughput. ACCPS provides a new technique for automating the full-case picking process (CPP) that contributes greatly to decreasing total operating cost by minimizing labor requirements, space requirements, and potential errors, and increasing productivity and efficiency. The structure of ACCPS, which is based on individual modules, can further increase the flexibility and the adaptability of the system.Entwurf eines zellbasierten vollautomatischen Full-Case-Kommissioniersystems Der Kommissionierungsprozess (OP) wird als die höchst arbeitsintensive und kostenaufwändige Tätigkeit in den Lagern betrachtet. Einige Autoren behaupten, dass der Kommissionierungsprozess für bis zu 55 % aller Betriebskosten in einem Lager dafür verantwortlich sein könnte. Dies könnte möglicherweise wichtiger sein für Unternehmen, die große Volumina von schnell bewegenden Waren behandeln. Full-case-picking Prozesse und Mischpaletten von verschiedenen Produkten aufzubauen sind teure und komplexe Tätigkeiten. Firmen suchen nach Technologien, um ihre Leistungsfähigkeit zu verbessern und die Betriebskosten von zusätzlichen Tätigkeiten die keine Wertschöpfung erbringen in ihren Lagern und Distributionszentren (DCs) zu reduzieren. Heutzutage stehen die Designer der Kommissioniersysteme vor großen Herausforderungen, aufgrund der steigenden Arbeitskosten, weniger Platz und häufigere kleine Aufträge mit kurzen Lieferzeiten. Deshalb sind ständige Forschungsbemühungen gewidmet, um die Suche nach neuen innovativen Kommissionierlösungen für Stückgüter, die die Betriebskosten verringern, die Produktivität erhöhen, die Raumausnutzung optimieren und die Kundenservice verbessern. Diese Dissertation präsentiert ein neues vollautomatisiertes Kommissioniersystem für Stückgüter (ACPS), das als automatisiertes zelluläres Case-picking-system (ACCPS) bezeichnet wird. Das neue System zeichnet sich durch die vollständige und dauerhafte Zugänglichkeit aller Lagerhaltung Einheiten (SKUs) im System, das einen strategischen höheren Durchsatz des Kommissionierungsprozesses ermöglicht. Dieses neue System könnte auf verschiedene Niveaus der Automation innerhalb von Lagern und DCs angewandt werden, und ist für eine breite Reihe von Lagerautomationsvoraussetzungen passend. Das vorgeschlagene Design besteht aus Speicherzellen mit demselben Design und Betriebsprinzip wie der vertikale Senkrechtförderer für Stückgüter, der auf einem Förderband installiert ist, um eine Lagerungslinie zu bilden. Mehrere Lagerungslinien werden sich durch einen Verteilförderer von der Einlassseite und durch einen Sammelförderer von der Ausgangsseite verbunden, um ein ACCPS Use-Case-Modell zu bilden. Das Konzept dieses neuen Systems basiert auf dem Konzept des Schachtkommissionsystems (A-Farm), um ein neues innovatives System zum Zuführen und Puffern von Stückgütern zu schaffen. ACCPS ist ein neues Konzept für eine vollständiges Stückgütern Schachtkommissionsystem mit dem Ziel, bessere Lösungen für Lagern und DCs, die sich mit einer großen Menge und niedrigen Vielfalt von Produkten befassen, die in Kunststoffkisten oder Tablare behandelt werden zur Verfügung zu stellen. ACCPS würde eine effiziente Lösung für viele Typen von Waren wie (Nahrung, Getränk, Lebensmittel, Molkerei, Blumen, Wurst, Bäckerei und andere) sein. Optimierung der Kommissionierungsprozesse, Minimierung der Betriebskosten und Steigerung der Effizienz sind die wichtigsten Ziele des neuen vorgeschlagenen Designs. Diese Forschung untersucht Layout, Design, Struktur, Kosten, Betriebsprinzipien, Zykluszeit und Durchsatz des neuen Systems. Ein einfacher Logik-Prozess wurde angewendet, um ein mathematisches Modell zu erstellen, damit die erwartete durchschnittliche Zeit der Kommissionierung und der Durchsatz von dieser neuen ACPS zu berechnet werden. Ein Simulationsmodell wurde entwickelt, um bei der Messung der Effektivität des vorgeschlagenen Designs der ACCPS unter realen Betriebsbedingungen zu unterstützen. Zwei Fallstudien sind verwendet worden, um die Leistung des neuen Systems zu bewerten. Gestützt auf den Echtzeitdaten dieser zwei Fälle, viele Simulation Szenarien wurden untersucht und analysiert um das Problem der Lagerplatzzuweisung zu beheben und die beste Strategie für die Kommissionierung zu bestimmen. Viele Optimierung Szenarien wurden simuliert und analysiert um das optimale Szenario zu bestimmen. Im Hinblick auf die Bewertung der Leistung des ACCPSs, wurde ein Vergleich zwischen ACCPS und ein alternatives System mit denselben Eigenschaften durchgeführt. Das Gantry Robot System (GRS), ist das alternative System für das am meist konkurrenzfähige System im Vergleich zum ACCPS. Die Kosten, der Durchsatz und die erforderliche Fläche wurden als die Hauptkriterien zum Vergleich zwischen den beiden Systemen gewählt. Der Vergleich hat die Vorteile des ACCPSs im Verringern der Betriebskosten, der erforderlichen Fläche, des Energieverbrauchs und der Entnahmezeit (Pickzeit) bestätigt. ACCPS stellt eine neue Technik zur Verfügung, um die Full-case-picking Prozessen (CPP) zu automatisieren, die außerordentlich zum Verringern von Gesamtbetriebskosten durch die Minderung von Arbeitskräftebedarf, Platzbedarf und potenziellen Fehlern, und die Erhöhung der Produktivität und Leistungsfähigkeit beiträgt. Die Struktur von ACCPS, die auf individuellen Modulen basiert, kann weiter die Flexibilität und die Anpassungsfähigkeit des Systems vergrößern

Production Engineering and Management

It is our pleasure to introduce the 8th edition of the International Conference on Production Engineering and anagement (PEM), an event that is the result of the joint effort of the OWL University of Applied Sciences and the University of Trieste. The conference has been established as an annual meeting under the Double Degree Master Program “Production Engineering and Management” by the two partner universities. This year the conference is hosted at the university campus in Lemgo, Germany. The main goal of the conference is to offer students, researchers and professionals in Germany, Italy and abroad, an opportunity to meet and exchange information, discuss experiences, specific practices and technical solutions for planning, design, and management of manufacturing and service systems and processes. As always, the conference is a platform aimed at presenting research projects, introducing young academics to the tradition of symposiums and promoting the exchange of ideas between the industry and the academy. This year’s special focus is on Supply Chain Design and Management in the context of Industry 4.0, which are currently major topics of discussion among experts and professionals. In fact, the features and problems of Industry 4.0 have been widely discussed in the last editions of the PEM conference, in which sustainability and efficiency also emerged as key factors. With the further study and development of Direct Digital Manufacturing technologies in connection with new Management Practices and Supply Chain Designs, the 8th edition of the PEM conference aims to offer new and interesting scientific contributions. The conference program includes 25 speeches organized in seven sessions. Two are specifically dedicated to “Direct Digital Manufacturing in the context of Industry 4.0”. The other sessions are covering areas of great interest and importance to the participants of the conference, which are related to the main focus: “Supply Chai n Design and Management”, “Industrial Engineering and Lean Management”, “Wood Processing Technologies and Furniture Production”, and “Management Practices and Methodologies”. The proceedings of the conference include the articles submitted and accepted after a careful double-blind refereeing process

A model based method for evaluation of crop operation scenarios in greenhouses

Abstract This research initiated a model-based method to analyse labour in crop production systems and to quantify effects of system changes in order to contribute to effective greenhouse crop cultivation systems with efficient use of human labour and technology. This method was gradually given shape in the discrete event simulation model GWorkS, acronym for Greenhouse Work Simulation. Model based evaluation of labour in crop operations is relatively new in greenhouse horticulture and could allow for quantitative evaluation of existing greenhouse crop production systems, analysis of improvements, and identification of bottlenecks in crop operations. The modelling objective was a flexible and generic approach to quantify effects of production system changes. Cut-rose was selected as a case-study representative for many cut-flowers and fruit vegetables. The first focus was a queueing network model of the actions of a worker harvesting roses in a mobile cultivation system. Data and observations from a state-of-art mobile rose production system were used to validate and test the harvesting model. Model experiments addressed target values of operational parameters for best system performance. The model exposed effects of internal parameters not visible in acquired data. This was illustrated for operator and gutter speed as a function of crop yield. The structure and setup of the GWorkS model was generic where possible and system specific where inevitable. The generic concept was tested by transferring GWorkS to harvesting a greenhouse section in a static growing system for cut-roses and extending it with navigation in the greenhouse, product handling, and multiple operator activity (up to 3 workers). Also for rose harvesting in a static growing system, the model reproduced harvesting accurately. A seven workday validation for an average skilled harvester showed a relative root mean squared error (RRMSE) under 5% for both labour time and harvest rate. A validation for 96 days with various harvesters showed a higher RRMSE, 15.2% and 13.6% for labour time and harvest rate respectively. This increase was mainly caused by the absence of model parameters for individual harvesters. Work scenarios were simulated to examine effects of skill, equipment, and harvest management. For rose yields of 0.5 and 3 harvested roses per m2, harvest rate was 346 and 615 stems h-1 for average skilled harvesters, 207 and 339 stems h-1 for new harvesters and 407 and 767 stems h-1 for highly skilled harvesters. Economic effects of trolley choice are small, 0-2 € per 1000 stems and two harvest cycles per day was only feasible if yield quality effects compensate for extra costs of 0.2-1.1 eurocents per stem. In a sensitivity analysis and uncertainty analysis, parameters with strong influence on labour performance in harvesting roses in a static system were identified as well as effects of parameter uncertainty on key performance indicators. Differential sensitivity was analysed, and results were tested for linearity and superposability and verified using the robust Monte Carlo method. The model was not extremely sensitive for any of the 22 tested input parameters. Individual sensitivities changed with crop yield. Labour performance was most affected by greenhouse section dimensions, single rose cut time, and yield. Throughput was most affected by cut time of a single rose, yield, number of harvest cycles, greenhouse length and operator transport velocity. In uncertainty analysis the coefficient of variation for the most important outputs labour time and throughput is around 5%. The main sources of model uncertainty were in parallel execution of actions and trolley speed. The uncertainty effect of these parameters in labour time, throughput and utilisation of the operator is acceptably small with CV less than 5%. The combination of differential sensitivity analysis and Monte Carlo analysis gave full insight in both individual and total sensitivity of key performance indicators. To realise the objective of model based improvement of the operation of horticultural production systems in resources constrained system, the GWorkS-model was extended for simultaneous crop operations by multiple workers analysis. This objective was narrowed down to ranking eight scenarios with worker skill as a central theme including a labour management scenario applied in practise. The crop operations harvest, disbudding and bending were considered, which represent over 90% of crop-bound labour time. New sub-models on disbudding and bending were verified using measured data. The integrated scenario study on harvest, disbudding and bending showed differences between scenarios of up to 5 s per harvested rose in simulated labour time and up to 7.1 € m-2 per year in labour costs. The simulated practice of the grower and the scenario with minimum costs indicated possible savings of 4 € m-2 per year, which equals 15% of labour cost for harvest, disbudding and bending. Multi-factorial assessment of scenarios pointed out that working with low skilled, low paid workers is not effective. Specialised workers were most time effective with -17.5% compared to the reference, but overall a permanent team of skilled generalists ranked best. Reduced diversity in crop operations per day improved labour organisational outputs but ranked almost indifferent. The reference scenario was outranked by 5 scenarios. Discrete event simulation, as applied in the GWorkS-model, described greenhouse crop operations mechanistically correct and predicts labour use accurately. This model-based method was developed and validated by means of data sets originating from commercial growers. The model provided clear answers to research questions related to operations management and labour organisation using the full complexity of crop operations and a multi-factorial criterion. To the best of our knowledge, the GWorkS-model is the first model that is able to simulate multiple crop operations with constraints on available staff and resources. The model potentially supports analysis and evaluation of design concepts for system innovation.</p

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering